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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Miniature L-Band Radar Transceiver

A miniature L-band transceiver that operates at a carrier frequency of 1.25 GHz has been developed as part of a generic radar electronics module (REM) that would constitute one unit in an array of many identical units in a very-large-aperture phased-array antenna. NASA and the Department of Defense are considering the deployment of such antennas in outer space; the underlying principles of operation, and some of those of design, also are applicable on Earth. The large dimensions of the antennas make it advantageous to distribute radio-frequency electronic circuitry into elements of the arrays. The design of the REM is intended to implement the distribution. The design also reflects a requirement to minimize the size and weight of the circuitry in order to minimize the weight of any such antenna. Other requirements include making the transceiver robust and radiation-hard and minimizing power demand. Figure 1 depicts the functional blocks of the REM, including the L-band transceiver. The key functions of the REM include signal generation, frequency translation, amplification, detection, handling of data, and radar control and timing. An arbitrary-waveform generator that includes logic circuitry and a digital-to-analog converter (DAC) generates a linear-frequency-modulation chirp waveform. A frequency synthesizer produces local-oscillator signals used for frequency conversion and clock signals for the arbitrary-waveform generator, for a digitizer [that is, an analog-to-digital converter (ADC)], and for a control and timing unit. Digital functions include command, timing, telemetry, filtering, and high-rate framing and serialization of data for a high-speed scientific-data interface. The aforementioned digital implementation of filtering is a key feature of the REM architecture. Digital filters, in contradistinction to analog ones, provide consistent and temperature-independent performance, which is particularly important when REMs are distributed throughout a large array. Digital filtering also enables selection among multiple filter parameters as required for different radar operating modes. After digital filtering, data are decimated appropriately in order to minimize the data rate out of an antenna panel. The L-band transceiver (see Figure 2) includes a radio-frequency (RF)-to-baseband down-converter chain and an intermediate- frequency (IF)-to-RF up-converter chain. Transmit/receive (T/R) switches enable the use of a single feed to the antenna for both transmission and reception. The T/R switches also afford a built-in test capability by enabling injection of a calibration signal into the receiver chain. In order of decreasing priority, components of the transceiver were selected according to requirements of radiation hardness, then compactness, then low power. All of the RF components are radiation-hard. The noise figure (NF) was optimized to the extent that (1) a low-noise amplifier (LNA) (characterized by NF < 2 dB) was selected but (2) the receiver front-end T/R switches were selected for a high degree of isolation and acceptably low loss, regardless of the requirement to minimize noise.

McWatters, Dalia↗
DOE OSTI2021

WHISPER: Wireless Home Identification and Sensing Platform for Energy Reduction

Many regions of the world benefit from heating, ventilating, and air-conditioning (HVAC) systems to provide productive, comfortable, and healthy indoor environments, which are enabled by automatic building controls. Due to climate change, population growth, and industrialization, HVAC use is globally on the rise. Unfortunately, these systems often operate in a continuous fashion without regard to actual human presence, leading to unnecessary energy consumption. As a result, the heating, ventilation, and cooling of unoccupied building spaces makes a substantial contribution to the harmful environmental impacts associated with carbon-based electric power generation, which is important to remedy. For our modern electric power system, transitioning to low-carbon renewable energy is facilitated by integration with distributed energy resources. Automatic engagement between the grid and consumers will be necessary to enable a clean yet stable electric grid, when integrating these variable and uncertain renewable energy sources. We present the WHISPER (Wireless Home Identification and Sensing Platform for Energy Reduction) system to address the energy and power demand triggered by human presence in homes. The presented system includes a maintenance-free and privacy-preserving human occupancy detection system wherein a local wireless network of battery-free environmental, acoustic energy, and image sensors are deployed to monitor homes, record empirical data for a range of monitored modalities, and transmit it to a base station. Several machine learning algorithms are implemented at the base station to infer human presence based on the received data, harnessing a hierarchical sensor fusion algorithm. Results from the prototype system demonstrate an accuracy in human presence detection in excess of 95%; ongoing commercialization efforts suggest approximately 99% accuracy. Using machine learning, WHISPER enables various applications based on its binary occupancy prediction, allowing situation-specific controls targeted at both personalized smart home and electric grid modernization opportunities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Uncertainty Quantification and Sensitivity Analysis of Non-Nuclear Advanced Controls Testbed Reactor Mockup

The research presented in this report describes our progress in applying stochastic methods and uncertainty quantification, parametric study, and variance-based sensitivity analysis (also known as Sobol sensitivity analysis) to a full-core model of a nuclear thermal propulsion (NTP) system simulated with Griffin, with the goal of developing a reduced order (surrogate) model which can be rapidly sampled while perturbing multiple input parameters. In this NTP system, reactivity and power feedback affect the rotation of control drums, which are controlled by a hybrid proportional, integral and derivative (PID) controller, actuated by the power demand and reactivity feedback from the numerical model. This model uses reactor kinetic feedback (mean generation time and $\beta$ from a transient Griffin simulation executed with the improved quasi-static method to provide the kinetic parameters) as inputs to functions which control the CD rotation angle. Using a number of stochastic method approaches, we developed a dual purpose training-surrogate model of the NTP system using polynomial regression. The trained model can be rapidly sampled while simultaneously perturbing various input parameters of the model, such as coefficients on the PID control, or temperature (directly affect the neutron cross section). The surrogate model delivers accurate results orders-of-magnitude faster (minutes, not days) than the base model. Once the base model has been trained, distributions of the uncertain parameters can be changed at will to investigate the effects of perturbing multiple inputs and their effect on the output. For example, coefficients used in the PID control system may vary due to some physical interference, or there may be uncertainty in the temperature of the neutron cross sections in various regions of the reactor. A distribution can be placed on these parameters and operational boundaries can be determined. The goal of this work is to support development of an advanced control system to operate CDs in a functioning NTP system.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Liquids-to-Power Using Low-Temperature Solid Oxide Fuel Cells

Solid oxide fuel cells (SOFCs) operating at high temperatures (>800°C) have been overlooked in the past for automotive applications, primarily due to their longer start-up times and inability to load follow (quickly respond to varying power demands). However, lower operating temperature SOFCs (LT-SOFCs) enable more rapid start-up and several other benefits. Additionally, the rapid deployment of cost-effective LT-SOFC technology for automotive applications relies on the utilization of conventional ‘‘drop-in’’ fuels (e.g., gasoline, diesel, ethanol etc.), that adapts the existing fuel distribution infrastructure. In particular, the liquid-fed LT-SOFCs have the potential to deliver higher “well-to-wheels” fuel conversion efficiencies than H 2 -fed fuel cells as well as take advantage of the higher fuel energy density. Therefore, this review focuses on the benefits/challenges of low-temperature SOFCs (350–650°C) running on liquid fuels. The critical role of anodes and requirements/status of advanced anode materials for the direct utilization of liquid fuels in LT-SOFCs are highlighted.

25 ENERGY STORAGE↗
DOE OSTI2024

The environmental impact of hydropower: a systematic review of the ecological effects of sub-daily flow variability on riverine fish

Hydropower can help facilitate power grid decarbonization because it can respond to short-term changes in power demand and is comparatively more reliable than intermittent wind and solar. However, flexible hydropower operations can create rapid and abnormal fluctuations in downstream flow conditions, which can negatively impact aquatic ecosystems. Accordingly, we conducted a systematic review on the ecological effects of hydropower-driven sub-daily flow variability (SDFV) on riverine fishes. We reviewed and synthesized 109 articles relevant to fish-SDFV relationships from seven sources, most of which focused on Salmonids in North America and northern and western Europe and were published in the last 15 years. We found strong agreement in the literature that SDFV increases fish stranding risk, destabilizes habitat, and decreases production and diversity. We found moderate agreement that SDFV interrupts fish reproduction, increases or has no impact on condition, and prompts or discourages movement depending on local channel conditions. We found little to no agreement for relationships between SDFV and mortality, physiology, and behavior. The effects of SDFV on riverine fish ecology are intertwined in the complex suite of biotic and abiotic characteristics that structure aquatic ecosystems and are highly site-, species-, and life stage-specific. Assessments of the impact of SDFV on fish ecology should first characterize local habitat and channel quality and fish community composition to identify specific, measurable ecological outcomes to sustain or enhance, and then design mitigation strategies tailored to those ecological objectives.

13 HYDRO ENERGY↗
DOE OSTI2023

Direct Alcohol Fuel Cells: A Comparative Review of Acidic and Alkaline Systems

In the last 20 years, direct alcohol fuel cells (DAFCs) have been the subject of tremendous research efforts for the potential application as on-demand power sources. Two leading technologies respectively based on proton exchange membranes (PEMs) and anion exchange membranes (AEMs) have emerged: the first one operating in an acidic environment and conducting protons; the second one operating in alkaline electrolytes and conducting hydroxyl ions. In this review, we present an analysis of the state-of-the-art acidic and alkaline DAFCs fed with methanol and ethanol with the purpose to support a comparative analysis of acidic and alkaline systems, which is missing in the current literature. A special focus is placed on the effect of the reaction stoichiometry in acidic and alkaline systems. Particularly, we point out that, in alkaline systems, OH – participates stoichiometrically to reactions, and that alcohol oxidation products are anions. This aspect must be considered when designing the fuel and when making an energy evaluation from a whole system perspective.

25 ENERGY STORAGE↗
DOE OSTI2020

Self-cleaning and de-pollution efficacies of photocatalytic architectural membranes

Photocatalytic self-cleaning “cool” roofs and walls can maintain high albedos, saving building cooling energy, reducing peak power demand, and mitigating the urban heat island effect. Other environmental benefits result from their de-polluting properties. Specimens from two different photocatalytic architectural membranes and a non-photocatalytic control were exposed alongside vertically, facing west, for two years at three California sites, and retrieved quarterly for testing. Photocatalytic materials showed excellent self-cleaning performance, retaining albedos of 0.74 – 0.75. By contrast, the control material exhibited an albedo loss of up to 0.10, with appreciable soiling observed by scanning electron microscopy. De-pollution capacity was assessed by quantifying NO removal and NOx deposition rates at 60 °C. Furthermore, efficacy varied with exposure location, weather conditions, and the nature of the photocatalytic material. Seasonal effects were observed, with partial inhibition during the dry season and reactivation during the rainy season.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Optimal deployment of thermal energy storage under diverse economic and climate conditions

This paper presents an investigation of the economic benefit of thermal energy storage (TES) for cooling, across a range of economic and climate conditions. Chilled water TES systems are simulated for a large office building in four distinct locations, Miami in the U.S.; Lisbon, Portugal; Shanghai, China; and Mumbai, India. Optimal system size and operating schedules are determined using the optimization model DER-CAM, such that total cost, including electricity and amortized capital costs are minimized. The economic impacts of each optimized TES system is then compared to systems sized using a simple heuristic method, which bases system size as fraction (50percent and 100percent) of total on-peak summer cooling loads. Results indicate that TES systems of all sizes can be effective in reducing annual electricity costs (5percent-15percent) and peak electricity consumption (13percent-33percent). The investigation also indentifies a number of criteria which drive TES investment, including low capital costs, electricity tariffs with high power demand charges and prolonged cooling seasons. In locations where these drivers clearly exist, the heuristically sized systems capture much of the value of optimally sized systems; between 60percent and 100percent in terms of net present value. However, in instances where these drivers are less pronounced, the heuristic tends to oversize systems, and optimization becomes crucial to ensure economically beneficial deployment of TES, increasing the net present value of heuristically sized systems by as much as 10 times in some instances.

25 ENERGY STORAGE↗
DOE OSTI2022

Predictive modeling of a subcritical pulverized-coal power plant for optimization: Parameter estimation, validation, and application

As renewable power generation deployment increases, fossil fuel plants are increasingly required to operate more flexibly. Many coal-fired power plants were originally designed to operate at base load and do not operate optimally at partial load. Predictive first-principles plant-wide models can be employed to identify opportunities for flexibility improvements and diagnose low-load operating issues. This paper describes the application of the Institute for the Design of Advanced Energy Systems Integrated Platform (IDAES) to model and optimize flexible power plant operations. The key benefits of using IDAES are that it provides an open-source, fully equation-oriented modeling framework for efficient modular model construction, reuse, and customization, together with a mathematical optimization framework leveraging powerful, state-of-the-art solvers. The process systems engineering workflow from predictive process simulation to parameter estimation, model validation, and plant optimization is applicable to a variety of existing and next-generation energy systems as well as other chemical and environmental processes. Here, to demonstrate this capability, a physics-based, steady-state model was developed to improve full- and part-load performance of the Escalante Generating Station, a 245 MWe (net) subcritical pulverized coal-fired power plant owned and operated by Tri-State Generation and Transmission Association. Specifically, sixty-nine model parameters were simultaneously estimated from several months of operating data enabling prediction of flow rates, temperatures, pressures, and steam quality throughout the plant. The validated model was leveraged by Escalante to reduce the minimum operating load from 90 MW to 50 MW by diagnosing a low-load water-hammer issue, enabling coal usage and emissions reductions during periods of low power demand. Additionally, opportunities for heat rate reduction (i.e., efficiency improvement) through a steeper sliding-pressure approach to load-following and optimization of other boiler operating variables were also identified and quantified. For example, a potential efficiency improvement of 0.7 percentage points was observed at half-load operation.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Levelized cost of charging of extreme fast charging with stationary LMO/LTO batteries

Extreme DC fast charging for electric vehicles (EVs) could be competitive with the internal combustion engine refueling experience and enable longer-distance travel, which could help with EV adoption and decarbonization, but these systems have high capital costs and extremely variable high-power demands. Behind-the-meter systems (BTMS) could support extreme-fast-charging (XFC) stations to increase nationwide adoption of EVs. Here, this study examines the optimal break-even levelized cost of charging (LCOC) across 96 BTMS scenarios to enable low-wait XFC stations providing 200 miles of charge in 10 min. This research simulates LCOC via synthetic XFC-capable EV loads, machine-learned battery life models from testing data, and nonlinear optimal controls, co-minimizing complex utility costs and battery replacements. An aggregate optimal BTMS design treating each EV load as equal likely gives an optimal LCOC per utility rate, the average of which is $\$$0.59/kWh. In addition, the sensitivity of optimal and off-optimal design factors, the long-life LMO/LTO chemistry, and optimized controls are analyzed. The battery control model, based on battery stressors to compare chemistries, optimizes LMO/LTO resting state of charge and cycle depth without compromising cost reduction, which enables greater flexibility in operation. The LCOC savings due to replacement reduction are small, up to $\$$0.035/kWh (6%), with an average of $\$$0.02/kWh (3.5%). Compared with gasoline stations, the aggregate XFC station design achieves comparable speed, experience of service, and cost at $\$$3.81/gal gasoline, showing that EVs can replace gasoline vehicles even for longer-distance travel.

25 ENERGY STORAGE↗
DOE OSTI2022

UV/chlorine advanced oxidation processes for degradation of contaminants in water and wastewater: A comprehensive review

Advanced oxidation processes (AOPs) have recently gained increasing attention as promising alternatives to conventional water and wastewater treatment technologies. As an AOP, there has been a growing interest in UV/chlorine due to its multiple disinfection modes and ability to maintain chlorine residuals in drinking water distribution systems. Compared to the popular UV/H 2 O 2 AOP treatment process, UV/chlorine AOP possesses several advantages including a higher radical production efficiency and a lower power demand. The process has recently been applied for the degradation of a wide range of natural and synthetic organic as well as inorganic compounds including pharmaceutical and personal care products, natural organic matter, herbicides and insecticides, taste and odor, and different types of water and wastewaters. The focus of the present work is to review and evaluate the efficiency of the UV/chlorine process on the oxidation of these pollutants. Here a critical overview is provided of the fundamentals of UV/chlorine, controlling factors of the process performance, and a comparison with other UV-based AOPs. The formation of disinfection by-products (DBPs), one of the concerns associated with UV/chlorine treatment, is discussed and strategies to tackle this obstacle are provided for future studies and applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Review of data-driven models for quantifying load shed by non-residential buildings in the United States

Shifting and shedding power demand in buildings can be cost-effective techniques for grids to function reliably and for end users to earn compensation. Grid operators reimburse customers in proportion to the quantity of load shed. Simple data-driven methods are used to quantify this shed, which is the difference between a measured load during the event and modeled "baseline" that would have occurred in absence of the event. These methods have evolved over the years and in many cases have been integrated with building physics, to make them a hybrid between physics based and empirical models. However, there is no comprehensive analysis that provides guidance to building operators, grid operators and researchers in selecting appropriate models based on their specific needs and available data. Here, this work aims to fill this gap by critically assessing the performance of baseline models put forward from the year 2000 through 2023. The literature reviewed includes reports generated by grid operators, reports from national laboratories and academic journal articles. The work outlines modeling features like the inputs, training period, estimation method, adjustments to fine tune the predictions and metrics to evaluate the performance. A comprehensive list of 50 models has been provided. For each model, the study explores the applicability of the model to weather sensitive buildings, variability in the building profile, timing of the event, and whether the building reduces energy consumption before an event. The work identifies the situations in which a particular model works and draws lessons based on evidence of performance. Finally, recommendations to aid in model selection are given.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Translational Science for Energy and Beyond

A clear challenge for the coming decades is decreasing the carbon intensity of the global energy supply while simultaneously accommodating a rapid worldwide increase in power demand. Meeting this challenge of providing abundant, clean energy undoubtedly requires synergistic efforts between basic and applied researchers in the chemical sciences to develop and deploy new technologies. Among the available options, solar energy is one of the promising targets because of the high abundance of solar photons over much of the globe. Similarly, decarbonization of the global energy supply will require clean sources of hydrogen to use as reducing equivalents for fuel and chemical feedstocks. In this report, we discuss the importance of translational research -- defined as work that explicitly targets basic discovery as well as technology development -- in the context of photovoltaics and solar fuels. We focus on three representative research programs encompassing translational research in government, industry, and academia. We then discuss more broadly the benefits and challenges of translational research models and offer recommendations for research programs that address societal challenges in the energy sector and beyond.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

High-Temperature Refractory Metasurfaces for Solar Thermophotovoltaic Energy Harvesting

Solar energy promises a viable solution to meet the ever-increasing power demand by providing a clean, renewable energy alternative to fossil fuels. For solar thermophotovoltaics (STPV), high-temperature absorbers and emitters with strong spectral selectivity are imperative to efficiently couple solar radiation into photovoltaic cells. We demonstrate refractory metasurfaces for STPV with tailored absorptance and emittance characterized by in situ high-temperature measurements, featuring thermal stability up to at least 1200 °C. Our tungsten-based metasurface absorbers have close-to-unity absorption from visible to near-infrared and strongly suppressed emission at longer wavelengths, while our metasurface emitters provide wavelength-selective emission spectrally matched to the band-edge of InGaAsSb photovoltaic cells. The projected overall STPV efficiency is as high as 18% when a fully integrated absorber/emitter metasurface structure is employed, which is comparable to the efficiencies of the best currently available commercial single-junction PV cells and can be further improved to potentially exceed those in mainstream photovoltaic technologies. Finally, our work opens a path forward for high-performance STPV systems based on refractory metasurface structures.

14 SOLAR ENERGY↗
DOE OSTI2023

Regulating Catalytic Properties and Thermal Stability of Pt and PtCo Intermetallic Fuel-Cell Catalysts via Strong Coupling Effects between Single-Metal Site-Rich Carbon and Pt

Developing low platinum-group-metal (PGM) catalysts for the oxygen reduction reaction (ORR) in proton-exchange membrane fuel cells (PEMFCs) for heavy-duty vehicles (HDVs) remains a great challenge due to the highly demanded power density and long-term durability. Here, this work explores the possible synergistic effect between single Mn site-rich carbon (Mn SA -NC) and Pt nanoparticles, aiming to improve intrinsic activity and stability of PGM catalysts. Density functional theory (DFT) calculations predicted a strong coupling effect between Pt and MnN 4 sites in the carbon support, strengthening their interactions to immobilize Pt nanoparticles during the ORR. The adjacent MnN 4 sites weaken oxygen adsorption at Pt to enhance intrinsic activity. Well-dispersed Pt (2.1 nm) and ordered L1 2 -Pt 3 Co nanoparticles (3.3 nm) were retained on the Mn SA -NC support after indispensable high-temperature annealing up to 800 °C, suggesting enhanced thermal stability. Both PGM catalysts were thoroughly studied in membrane electrode assemblies (MEAs), showing compelling performance and durability. The Pt@Mn SA -NC catalyst achieved a mass activity (MA) of 0.63 A mg Pt –1 at 0.9 V iR-free and maintained 78% of its initial performance after a 30,000-cycle accelerated stress test (AST). The L1 2 -Pt 3 Co@Mn SA -NC catalyst accomplished a much higher MA of 0.91 A mg Pt –1 and a current density of 1.63 A cm –2 at 0.7 V under traditional light-duty vehicle (LDV) H 2 –air conditions (150 kPa abs and 0.10 mg Pt cm –2 ). Furthermore, the same catalyst in an HDV MEA (250 kPa abs and 0.20 mg Pt cm –2 ) delivered 1.75 A cm –2 at 0.7 V, only losing 18% performance after 90,000 cycles of the AST, demonstrating great potential to meet the DOE targets.

25 ENERGY STORAGE↗
DOE OSTI2015

Evidence of covalent synergy in silicon–sulfur–graphene yielding highly efficient and long-life lithium-ion batteries

Silicon has the potential to revolutionize the energy storage capacities of lithium-ion batteries to meet the ever increasing power demands of next generation technologies. To avoid the operational stability problems of silicon-based anodes, we propose synergistic physicochemical alteration of electrode structures during their design. This capitalizes on covalent interaction of Si nanoparticles with sulfur-doped graphene and with cyclized polyacrylonitrile to provide a robust nanoarchitecture. This hierarchical structure stabilized the solid electrolyte interphase leading to superior reversible capacity of over 1,000 mAh g -1 for 2,275 cycles at 2 A g -1 . Furthermore, the nanoarchitectured design lowered the contact of the electrolyte to the electrode leading to not only high coulombic efficiency of 99.9% but also maintaining high stability even with high electrode loading associated with 3.4 mAh cm -2 . As a result, the excellent performance combined with the simplistic, scalable and non-hazardous approach render the process as a very promising candidate for Li-ion battery technology.

36 MATERIALS SCIENCE↗