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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

ENERGY STAR Residential Water Heater Specification and Test Method for Connected Residential Water Heaters

Electric water heaters have long been used as a tool for demand response due to their inherent thermal storage and large electric load. Traditionally, electric water heaters have been controlled by external load control switches, but that type of control does not work well with more efficient heat pump water heaters and cannot ensure that consumers have adequate hot water. Water heater manufacturers are adding more sophisticated controls that allow utilities or consumers to control their water heaters in new ways that can provide demand response without impacting consumer comfort. Further, the electric utility grid has seen a rapid increase the availability of renewable energy, which, depending on the type of renewable energy, can provide large amounts of energy for a portion of the day, but reduced or no energy at other times. In response to these advances in controls, availability of periodic renewable energy, and in an effort to have a standard which can be applied at a national level, ENERGY STAR and the Department of Energy have developed a Product Specification and Test Method for Connected Residential Water Heaters. In this session, we will discuss the new specification and test method, as well as show some initial results from running the new test method with two different HPWHs at NREL.

connected water heater↗
DOE OSTI2022

A novel approach for produced water treatment: Supercritical water oxidation and desalination

Produced water generated from oil and gas operations contains significant quantities of environmentally hazardous hydrocarbons, organic chemicals, and inorganic salts. Environmental regulations with impaired water disposal mandates produced water treatment and desalination. Industry standard desalination technologies are energy-intensive and mandate extensive produced water pre-treatment including removal of hydrocarbons constituents for efficient operations. Herein this study investigates a novel process intensification approach integrating supercritical water oxidation (SCWO) unit operation with a supercritical water desalination (SCWD) process for energy efficient produced water treatment and desalination. The coupled SCWD-SCWO process is found to be very energy-efficient and cost effective than existing industry standard desalination technologies. For energy efficient operation, the heat generated from the SCWO of hydrocarbons present in the produced water is used for power generation using a high efficiency and low-cost re-heat Rankine cycle process. The cost of treating produced water with proposed SCWO-SCWD process is independent of the salt concentration. The proposed process has the potential to offer step-change improvements over conventional processes in both the efficiency and cost of produced water treatment: for example, a cost and energy saving of 70% and 100% is calculated for the treatment of produced water containing 250 g/l salt and 10.6 g/l hydrocarbon.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A Method to Design and Optimize Axial Flow Cyclones for Gas–Liquid Separation

This article provides a detailed design guide, optimization, and performance assessment for air–water separation of an axial flow cyclone. Axial flow cyclones (also known as swirl tube demisters, mist eliminators, or Austin–Write cyclones) have a range of applications in several different industries. This method of gas–liquid separation offers many benefits. Among these are high liquid separation efficiencies (near 99%) and an inline design that allows them to be more easily fitted into existing piping structures. Despite these benefits, there are several design parameters that have not been optimized for performance in wastewater purification applications. This research fills the gap in the literature by quantifying the effect of new design parameters on water collection efficiency, η water collection , and the air bypass efficiency, η air bypass , defined as the ratio of the air mass flowrate exiting through the desired air outlet over the inlet air mass flowrate. A set of wide-ranging experiments were conducted to study the effects of gas–liquid flow rates, tube geometry, and relative injection angles to optimize the water collection and air bypass efficiencies. The water collection efficiency exceeded 99.8% when the liquid streamline came in direct contact with the water drainage exit. An empirical correlation was developed to predict the swirl pitch as a function of the above design parameters. Predictions from the correlation were within 10% of the experimental results. The correlation can be used to design highly efficient in-line gas–liquid separators.

Engineering↗
DOE OSTI2024

Residential Integrated Heat Pump to Meet All the Home Comfort Needs

This paper will introduce development and field trial of a residential air-source integrated heat pump for cold climates. The heat pump is multi-functional to meet all the home comfort demands, including space cooling, space heating, domestic water heating. The integrated heat pump is an ideal solution to decarbonize northern homes via providing efficient space heating and water heating to replace natural gas. It uses a three-stage compressor and a single set of heat exchangers and valves to deliver all the functions, and thus achieve cost reduction. We developed an innovative system configuration and related controls to solve typical charge unbalance, accelerate charge migration and smoothen mode transition in integrated heat pumps. Laboratory investigations were conducted for individual modes and verified the control functions. Laboratory tests demonstrated that the unit delivered outstanding performance. It achieved 17.0 SEER (seasonal cooling energy efficiency rating) and 11.0 HSPF (heating seasonal performance factor). In the most efficient mode (combined space cooling and water heating mode), the unit reached a total energy efficiency > 30.0 EER and required only 25 minutes to heat a 50-gallon tank of water. One heat pump prototype is going through a field trial since April, 2023 in Syracuse, New York. The one-year field test results are summarized.

Shen, Bo↗
DOE OSTI2023

HydroGEN and H2NEW Data Hub

HydroGEN is a multi-lab consortium focused on early-stage R&D in H2 production, supported by the U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy (EERE), Hydrogen and Fuel Cell Technologies Office (HFTO). The consortium advances research and development (R&D) of innovative materials for advanced water splitting (AWS) technologies to enable clean, sustainable and low-cost ($1/kg H2) hydrogen production and fosters cross-cutting innovation using theory-guided applied materials R&D to advance all emerging water-splitting pathways for hydrogen production. Hydrogen from Next-generation Electrolyzers of Water (H2NEW) is a consortium of nine U.S. Department of Energy (DOE) national laboratories focused on making large-scale electrolyzers, which produce hydrogen from electricity and water, more durable, efficient, and affordable. The presentation introduces the HydroGEN data hub to the H2NEW consortium and encourages H2NEW members to use it to store and share data with team members and eventually the public. The two consortia share this data hub.

advanced water splitting technologies↗
DOE OSTI2021

Highly Efficient Surface Charge Transfer in Fe 2 TiO 5 Epitaxial Thin Film Photoanodes

Pseudobrookite (Fe 2 TiO 5 ) has attracted significant attention as an emerging photoanode for water oxidation due to reports of enhanced performance in polycrystalline heterostructures with α-Fe 2 O 3 or TiO 2 . However, the specific properties and contribution of Fe 2 TiO 5 remain unknown. Here, we present the first photoelectrochemical characterization of epitaxial thin film Fe 2 TiO 5 , an ideal platform for probing the inherent response of this earth-abundant photoanode for solar water splitting. Moreover, by using an electrolyte containing a hole scavenger, we find highly efficient charge transfer at the Fe 2 TiO 5 –electrolyte interface. This notable surface property is exploited in the form of an Fe 2 TiO 5 /α-Fe 2 O 3 heterostructure photoanode, for which we observe a photocurrent density increase by 1 order of magnitude and an onset potential improvement by ~300 mV. Establishing these fundamental properties elucidates the nature of reaction mechanisms on Fe 2 TiO 5 and informs the design of highly efficient water photo-oxidation devices by incorporating this material with other photoanodes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Ion-capture electrodialysis using multifunctional adsorptive membranes

Technologies that can efficiently purify nontraditional water sources are needed to meet rising global demand for clean water. Water treatment plants typically require a series of costly separation units to achieve desalination and the removal of toxic trace contaminants such as heavy metals and boron. We report a series of robust, selective, and tunable adsorptive membranes that feature porous aromatic framework nanoparticles embedded within ion exchange polymers and demonstrate their use in an efficient, one-step separation strategy termed ion-capture electrodialysis. This process uses electrodialysis configurations with adsorptive membranes to simultaneously desalinate complex water sources and capture diverse target solutes with negligible capture of competing ions. Our methods are applicable to the development of efficient and selective multifunctional separations that use adsorptive membranes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Integrating Applied Energy and BER Smart Data Capabilities to Develop a DOE Data Fabric for Energy-Water R&D

Focal Area(s): 1) Data acquisition and assimilation enabled by machine learning, AI, and advanced methods including experimental/network design/optimization, unsupervised learning (including deep learning), and hardware-related efforts involving AI (e.g., edge computing). Science Challenge: DOE R&D, including DOE’s Basic Energy Research (BER)’s Environmental Systems Science Division (EESSD) program and DOE’s applied energy research (AER) programs (EERE, FE, and NE) are producers and consumers of Earth systems datasets. This white paper focuses on the first topic area from the call in relation to how crosscutting resources and innovations from DOE’s EESSD and AER can be brought to bear to mutual benefit and more efficient energy-water, Earth system data resources through improved. The overarching challenge posed by this call focuses on how DOE can directly leverage artificial intelligence (AI) to engineer a substantial (paradigm-changing) improvement in Earth System Predictability? While stemming from DOE BER’s EESSD program, this is a challenge that is faced and also being addressed by DOE’s AER programs. Over the past decade plus, FE, EERE, and NE programs have made important strides towards addressing this need. These strides are in many ways highly complementary to EESSD’s MODEX efforts. Energy water systems spanning metocean to groundwater to surface water systems all are data driven whether for basic energy or applied energy. These are remote, multi-variate, complex natural, and in many cases engineered, systems. Key needs and challenges of both EESSD and AER include developing data-focused tools to enhance data search and discovery to fill in knowledge gaps (address sparse data challenge), and rapidly transform datasets, including disparate and multi-source data. Leveraging DOE on-premise computing (HPC, exascale) infrastructure supports the computing-intensive algorithms required to execute these data acquisition and transformation processes to derive enriched knowledge and data, driving AI/ML and big data analytics for these systems. The opportunity lies in combining BER and AER efforts to provide a more robust, advanced, efficient and complete computing data fabric to address energy-water data acquisition and assimilation needs which currently pose significant impediments to AI/ML predictions and research.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Cold Climate Integrated Heat Pump

This paper introduces development of a residential air-source integrated heat pump for cold climates (CCIHP). The heat pump is multi-functional to meet all the home comfort demands, including space cooling, space heating, domestic water heating and energy storage. The CCIHP is an ideal solution to decarbonize northern homes via providing efficient space heating and water heating to replace natural gas. It uses a three-stage compressor and a single set of heat exchangers and valves to deliver all the functions, and thus achieve cost reduction. We developed an innovative system configuration and related controls to solve typical charge unbalance in heat pumps, accelerate charge migration and smoothen mode transition in integrated heat pumps. Laboratory investigations were conducted for individual modes and verified the control functions. Laboratory tests demonstrated that the unit delivered outstanding performance. It achieved 17.0 SEER (seasonal cooling energy efficiency rating) and 11.0 HSPF (heating seasonal performance factor). In the most efficient mode (combined space cooling and water heating mode), the unit reached a total energy efficiency of 35.0 EER and required only 25 minutes to heat a 50-gallon tank of water. The CCIHP can heat 1.7 GPM water from 58 to 125°F in a direct flow-through, when the ambient temperature is above 47°F. In a dedicated water heating mode using outdoor air source, the heat pump operated down to 17°F, achieving a COP > 2.6, and heated 50-gallon water within 1 hour.

Shen, Bo↗
DOE OSTI2025

Predicting Initial Trans-Membrane Pressure for Optimized Operations in UF Unit Using Random Forest

With the growing scarcity of freshwater, innovative process design mechanisms like Ultra-filtration(UF) units are increasingly gaining attention among water treatment utilities to address the rising demand. Ensuring reliable water production necessitates efficient resource utilization, minimizing downtime in UF systems. Recent advancements in machine learning (ML) have enabled the development of accurate data-driven models for Model Predictive Control (MPC), often requiring minimal prior knowledge of underlying physical processes. In this study, we present predictive regression models based on Random Forest (RF) and Auto-Regressive (AR) approaches to forecast the initial Trans-Membrane Pressure (TMP) for each filtration cycle in data generated by Direct Potable Reuse (DPR) systems. The proposed RF-based model demonstrates superior performance compared to baseline methods, including historical mean, Last Observation Carried Forward (LOCF), and naïve AR models, across various forecasting horizons in terms of root mean square (RMSE) metric. Accurate prediction of initial TMP is critical for optimizing CCRO operations, as it enables the development of robust modelling frameworks that enhance process efficiency and reliability. The demonstrated efficacy of the RF-based approach highlights its potential as a tool for real-time decision-making in water treatment systems, paving the way for advanced process optimization and sustainable water resource management.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗
DOE OSTI2025

Electron Beam Irradiation for Water Treatment of Per- and Polyfluoroalkyl Substances (PFAS)

Per- and polyfluoroalkyl substances (PFAS) are widely used but are now considered a water contamination risk. Fermi National Accelerator Laboratory’s IARC group has demonstrated that passing water through electron beam radiation can destroy PFAS. This project aims to develop a process to scale the system for bulk water treatment. The key is efficient radiation usage, ensuring that all water receives only the minimum dose. Software was developed for this purpose, consisting of a computational fluid dynamics model (CFD) in COMSOL, which calculates particle trajectories through the radiation area. A MATLAB script integrates the radiation dose of these particles, and statistical analysis is performed to evaluate the radiation utilization efficiency. These models are validated with a flow test where colored dye is injected and optically tracked. Radiation dose is measured by testing under an e-beam to measure the degradation of a PFAS analog.

Mueller, Scott [Northern Illinois U.]↗
DOE OSTI2020

Climate-Water Impacts on Interconnection-Scale Electricity System Planning

A growing literature emphasizes the importance of integrating climate change impacts into electricity system planning. Rising average temperatures can increase and shift electricity demand while reducing generator and transmission efficiency. Changes to water availability and quality can reduce the output of thermally cooled generators and hydropower. Electric power grids across the US and globally are undergoing transformational changes that present new opportunities and challenges to reliability assurance. However, electric utilities and system operators have limited internal capabilities to incorporate these effects into planning practices. This work addresses gaps in utility and system planner practices by integrating climate-water-electricity expertise from universities and U.S. Department of Energy National Laboratories with electricity system planners and stakeholders in the Western Electricity Coordinating Council (WECC). Using a highly collaborative approach, global climate model data, high-resolution hydrology models, and long-term electric sector capacity expansion tools are employed to analyze a range of climate outcomes for future electricity scenarios aligned with recent WECC planning studies. Doing so allows WECC to expand its climate-agnostic planning assessments to consider how future temperature and precipitation patterns could influence generation and transmission planning. We explore how changes to climate-water conditions can affect power plant investment and operation, system economics, and environmental impacts, providing an expanded perspective on interconnection-wide decision making under climate uncertainty.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Predicting Initial Trans-Membrane Pressure for Optimized Operations in UF Unit Using Random Forest

With the growing scarcity of freshwater, innovative process design mechanisms like Reverse Osmosis (RO) are increasingly gaining attention among water treatment utilities to address the rising demand. Ensuring reliable water production necessitates efficient resource utilization, minimizing downtime in (ultra-filtration) UF systems. Recent advancements in machine learning (ML) have enabled the development of accurate data-driven models for Model Predictive Control (MPC), often requiring minimal prior knowledge of underlying physical processes. In this study, we present predictive regression models based on Random Forest (RF) and Auto-Regressive (AR) approaches to forecast the initial Trans-Membrane Pressure (TMP) for each filtration cycle in data generated by Direct Potable Reuse (DPR) systems. The proposed RF-based model demonstrates superior performance compared to baseline methods, including historical mean, Last Observation Carried Forward (LOCF), and naïve AR models, across various forecasting horizons in terms of root mean square error (RMSE) metric. To evaluate how different classes of process variables contribute to TMP dynamics over time, we examine the feature importance of independent covariates across multiple forecast horizons. This analysis provides insight into the temporal relevance of operational and sensor-derived features, guiding control and monitoring strategies. Additionally, the impact of hyperparameter tuning on TMP prediction performance is studied for both direct and recursive RF modelling approaches across increasing forecast horizons. Accurate prediction of initial TMP is critical for optimizing RO operations, as it enables the development of robust modelling frameworks by accurately estimating membrane fouling trends, thereby enhancing process efficiency and long-term reliability. The demonstrated efficacy of the RF-based approach highlights its potential as a tool for real-time decision-making in water treatment systems, paving the way for advanced process optimization and sustainable water resource management.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗
DOE OSTI2020

3D-Printed Membranes with a Zwitterionic Hydrogel Coating for More Robust Oil–Water Separation

Three-dimensional (3D)-printed membranes via stereolithography (SLA) are promising in oil–water separation, which is the key in the purification of industrial oily wastewater. To achieve gravity-driven oil–water separation, the membrane material needs to be simultaneously hydrophilic/oleophobic. However, most of the state-of-the-art materials for SLA do not meet the requirement. While water-adsorbing hydrogel is simultaneously hydrophilic/oleophobic and there have been reports on 3D printing of hydrogels in biomedical applications, the hydrogel is too soft for membrane application. Here, we report a simple approach to tackle the issue: a hydrogel coating on SLA-based plastic membranes. The coating is fabricated, using [2-(methacryloyloxy) ethyl] dimethyl-(3-sulfopropyl) ammonium hydroxide as the zwitterionic monomer and acrylamide as the comonomer, via in situ polymerization on SLA-based plastic membranes. The contact angle tests and Fourier transform infrared spectrum show that such a membrane readily adsorbs water and becomes simultaneously hydrophilic/oleophobic. The oil–water separation tests indicate that the water-adsorbed membrane is highly efficient in gravity-driven oil–water separation in 31 repeating cycles. Our results indicate the great potential of 3D-printed membranes in oil–water separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Advanced Electrocatalysis for Energy and Environmental Sustainability via Water and Nitrogen Reactions

Abstract Clean and efficient energy storage and conversion via sustainable water and nitrogen reactions have attracted substantial attention to address the energy and environmental issues due to the overwhelming use of fossil fuels. These electrochemical reactions are crucial for desirable clean energy technologies, including advanced water electrolyzers, hydrogen fuel cells, and ammonia electrosynthesis and utilization. Their sluggish reaction kinetics lead to inefficient energy conversion. Innovative electrocatalysis, i.e., catalysis at the interface between the electrode and electrolyte to facilitate charge transfer and mass transport, plays a vital role in boosting energy conversion efficiency and providing sufficient performance and durability for these energy technologies. Herein, a comprehensive review on recent progress, achievements, and remaining challenges for these electrocatalysis processes related to water (i.e., oxygen evolution reaction, OER, and oxygen reduction reaction, ORR) and nitrogen (i.e., nitrogen reduction reaction, NRR, for ammonia synthesis and ammonia oxidation reaction, AOR, for energy utilization) is provided. Catalysts, electrolytes, and interfaces between the two within electrodes for these electrocatalysis processes are discussed. The primary emphasis is device performance of OER‐related proton exchange membrane (PEM) electrolyzers, ORR‐related PEM fuel cells, NRR‐driven ammonia electrosynthesis from water and nitrogen, and AOR‐related direct ammonia fuel cells.

Li, Yi↗
DOE OSTI2021

Self-powered Heating: Efficiency Analysis

Conventional fuel-fired heating devices such as furnaces, boilers, and water heaters have fuel efficiency less than 100% on the basis of higher heating value. They also require electricity from the electric grid to power parasitic loads such as blowers, pumps, fans, and ignitors. The primary energy efficiency of the device accounts for both fuel used on-site and primary energy used off-site to produce electric power used by the device. This work compares conventional fuel-fired heating devices to two types of self-powered devices. A self-powered device (SPD) integrates a power cycle onboard to eliminate consumption of grid electricity. We assume that all heat rejected by the onboard power cycle is added to the process fluid, so that, compared with a conventional device, the same amount of heat is provided to the process fluid and the same amount of fuel is consumed, but grid electricity consumption is eliminated. The first SPD type is the basic one: exactly the electricity required is generated. The second type considered is the SPD with heat pump (SPD-HP), in which the power cycle generates more electricity than needed for parasitic loads, and the excess electricity is used to power a heat pump. The heat pump extracts additional heat from the ambient to boost efficiency. Both SPD and SPD-HP self-consume all the generated electricity, in contrast to combined heat and power (CHP) systems that export electricity. In this work, equations are derived to express the efficiency of three classes of heating devices: conventional (consuming grid electricity), self-powered (consuming no grid electricity), and self-powered with heat pump. The efficiency of each is derived as a function of up to six factors: (1) the fraction of combustion heat captured, (2) the rate of parasitic power consumption, (3) the fraction of electric energy dissipated as useful heat, (4) the power cycle conversion efficiency, (5) the grid efficiency, when applicable, and (6) the heat pump COP, when applicable. Scenarios are identified in which it is possible to achieve efficiency greater than 100% on a higher heating value basis. Plausible configurations using existing technology options are outlined.

Gluesenkamp, Kyle↗