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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

PBI nanofiber mat-reinforced anion exchange membranes with covalently linked interfaces for use in water electrolysers

Anion exchange membranes (AEM) are key components in anion exchange membrane water electrolysers. Recently developed materials are less susceptible to the alkaline degradation of the polymer backbone and quaternary ammonium groups. A remaining challenge is the mechanical stability in contact with hot water and dimensional stability when the temperature of the feed solution changes. One solution is to reinforce membranes with a porous support. Since support materials like PEEK or PTFE have a different swelling behavior than the matrix and no strong interactions with the matrix, voids can form, and gas crossover increases. In this work, we approach this issue by pore filling polybenzimidazole nanofiber mats with the bromomethylated precursor of mTPN, an ultra-stable AEM material. During drying, a covalent interaction between support (PBI amine groups) and matrix (-CH 2 Br) is established. After quaternization, the optimized PBI/mTPN-50.120 composite membrane still shows a high conductivity of 62 mS cm –1 , but 37% reduced length swelling in comparison to the non-reinforced membrane. Tensile strength and Young's modulus increase 17% and 56% to 49 MPa and 680 MPa, respectively. In an electrolyser, a stable voltage of 1.98V at 0.25 A cm –2 was achieved, and no change in membrane resistance was observed over the test time of 200 h (50°C, 1 M KOH, catalysts based on Ni/Fe and Mo).

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

Competitiveness Assessment of Decarbonizing Electricity and Process Heat Supply to a Campus with a Small Nuclear Reactor

This paper analyzes the competitiveness of siting a small nuclear reactor to support decarbonization of sites requiring tens of MW of electricity and/or process heat to support centralized heating and cooling system. This paper focuses on campuses as representative of sites with collections of buildings and research facilities with decarbonization needs represented by buildings heating, and electricity consumption by electrical loads which may include cooling via chilled water (e.g., for air conditioning and to cool down computer clusters). A nuclear reactor can be considered to decarbonize a site’s high-temperature steam generation used mostly for building heating needs, climate control, and hot water, by supplying process heat capabilities, while electricity decarbonization would be achieved mostly by the grid. However, a secondary application can be considered to maximize reactor utilization and avoid ramping down the reactor if the steam demand varies significantly throughout the year. Chilled water generation through steam-driven systems was identified as an attractive secondary option for the site analyzed, due to potential for plant design simplification, while electricity generation could be considered as well to reduce electricity purchases for a wider range of site applications. For a campus with peak 60MW thermal power demand, a small nuclear reactor with similar thermal power rating would almost eliminate CO2 emissions from steam generation and reduce electricity imports for chilled water production. A preliminary techno-economic feasibility study shows that a small nuclear reactor design that is optimized to support process heat can represent an economically feasible option when compared with other decarbonization alternatives.

Stauff, Nicolas E.↗
DOE OSTI2023

Assessing residential activity in a home plumbing system simulator: monitoring the occurrence and relationship of major opportunistic pathogens and phagocytic amoebas

Opportunistic premise plumbing pathogens (OPPPs) have been detected in buildings’ plumbing systems causing waterborne disease outbreaks in the United States. In this study, we monitored the occurrence of OPPPs along with free-living amoeba (FLA) and investigated the effects of residential activities in a simulated home plumbing system (HPS). Water samples were collected from various locations in the HPS and analyzed for three major OPPPs: Legionella pneumophila, nontuberculous mycobacterial species (e.g., Mycobacterium avium, M. intracellulare, and M. abscessus), and Pseudomonas aeruginosa along with two groups of amoebas (Acanthamoeba and Vermamoeba vermiformis). A metagenomic approach was also used to further characterize the microbial communities. Results show that the microbial community is highly diverse with evidence of spatial and temporal structuring influenced by environmental conditions. L. pneumophila was the most prevalent pathogen (86% of samples), followed by M. intracellulare (66%) and P. aeruginosa (21%). Interestingly, M. avium and M. abscessus were not detected in any samples. The data revealed a relatively low prevalence of Acanthamoeba spp. (4%), while V. vermiformis was widely detected (81%) across all the sampling locations within the HPS. Locations with a high concentration of L. pneumophila and M. intracellulare coincided with the highest detection of V. vermiformis, suggesting the potential growth of both populations within FLA and additional protection in drinking water. After a period of stagnation lasting at least 2-weeks, the concentrations of OPPPs and amoeba immediately increased and then decreased gradually back to the baseline. Furthermore, monitoring the microbial population after drainage of the hot water tank and partial drainage of the entire HPS demonstrated no significant mitigation of the selected OPPPs. This study demonstrates that these organisms can adjust to their environment during such events and may survive in biofilms and/or grow within FLA, protecting them from stressors in the supplied water.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Deep Reinforcement Learning Based Smart Water Heater Control for Reducing Electricity Consumption and Carbon Emission

Water heating is the third largest electricity consumer in U.S. households, after space heating and cooling. Thus, water heaters represent a significant potential for reducing electricity consumption and associated CO2 emissions of residential buildings. To this end, this study proposes a model-free deep reinforcement learning (RL) approach that aims to minimize the electricity consumption and the CO2 emissions of a heat pump water heater without affecting user comfort. In this approach, a set of RL agents focusing on either electricity saving or emission reduction, with different look ahead periods, were trained using the deep Q-networks (DQN) algorithm and their performance was tested on different hot water usage and Marginal Operating Emissions Rate (MOER) profiles. The testing results showed that the RL agents that focus on electricity saving can save electricity in the range of 12–22% by operating the water heater with maximum heat pump efficiency and minimum electric element utilization. On the other hand, the RL agents that focus on emission reduction reduced emissions in the range of 18–37% by making use of the variable MOER values. These RL agents used the heat pump and/or an element when the MOER values are low due to the availability of renewable energy sources (e.g., solar and wind) and mostly avoided the periods of carbon-intensive periods. Overall, these results showed that the proposed RL approach can help minimize the electricity consumption and the CO2 emissions of a heat pump water heater without having any prior knowledge about the device.

Amasyali, Kadir↗
DOE OSTI2024

Searching for Suitable Binary Fluid for an Ejector Heat Pump for Domestic Water Heating

Water heating is a major source of energy consumption in the U.S. residential sector. Heat pumps can significantly increase the energy efficiency of water heating. An ejector heat pump (EHP) is a novel, thermally driven heat pump that uses an ejector as a thermocompressor. Choosing suitable working fluids is critical in developing high-performance EHPs. Therefore, this research screens binary fluid pairs (BFPs) for EHPs to produce domestic hot water at a high coefficient of performance (COP). The criteria for screening BFP candidates for EHP water heaters (EHPWHs) are established, and BFP candidates are shortlisted. This study identifies HFE7000, Novec649, HFE7100, HFE7200, and HFE7500 for the primary fluids and RE170, R600a, R600, and R1234ze(Z) for the secondary fluids. The thermodynamic model is employed to investigate the performance of EHPWHs using the shortlisted BFPs under various operating parameters, including the evaporation pressure of the primary working fluid in the high-temperature evaporator and the condensation temperature. In conclusion, the highest heating-cycle COP of 1.328 is achieved by an EHPWH operating with HFE7000/R600 at a condenser temperature of 50 °C and a pressure of 1.69 MPa in the high-temperature evaporator.

42 ENGINEERING↗
DOE OSTI2021

Deep Reinforcement Learning for Autonomous Water Heater Control

Electric water heaters represent 14% of the electricity consumption in residential buildings. An average household in the United States (U.S.) spends about USD 400–600 (0.45 ¢/L–0.68 ¢/L) on water heating every year. In this context, water heaters are often considered as a valuable asset for Demand Response (DR) and building energy management system (BEMS) applications. To this end, this study proposes a model-free deep reinforcement learning (RL) approach that aims to minimize the electricity cost of a water heater under a time-of-use (TOU) electricity pricing policy by only using standard DR commands. In this approach, a set of RL agents, with different look ahead periods, were trained using the deep Q-networks (DQN) algorithm and their performance was tested on an unseen pair of price and hot water usage profiles. The testing results showed that the RL agents can help save electricity cost in the range of 19% to 35% compared to the baseline operation without causing any discomfort to end users. Additionally, the RL agents outperformed rule-based and model predictive control (MPC)-based controllers and achieved comparable performance to optimization-based control.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Simulation-based assessment of ASHRAE Guideline 36, considering energy performance, indoor air quality, and control stability

This study assesses American Society of Heating, Refrigerating and Air-Conditioning Engineers Guideline 36 (G36) with a typical medium office building. Specifically, this study employed a Modelica model of a variable air volume (VAV) system that serves this building, which includes components for representing indoor virus transmission and filtration. It then implemented the G36 control sequences for both water-side and air-side equipment in Python. After that, this study conducted the assessment by co-simulating G36 and the Modelica model using the Building Operations Testing Framework. Unlike existing works, this work has three unique features: (1) It considers the interactions between control sequences for water-side and air-side equipment of the studied VAV system. (2) It assesses the performance of G36 from the perspective of IAQ. (3) It examines the short-term behaviors of the studied building under G36 to understand the control stability. This assessment confirms significant energy savings from G36, largely because of the interaction between supply air temperature and hot water controls. It also reveals a trade-off between the ability to slow the spread of virus and the energy performance via demand controlled ventilation. Lastly, it emphasizes the necessity of tuning local feedback control when implementing G36.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Evacuations: Reva Hurwitz, The Red Cross, and Operation Crossroads

On April 1, 1946, an earthquake off Unimak Island, Alaska, generated a tsunami that raced across the Pacific. One of the islands in danger was Kwajalein, the logistical hub for Operation Crossroads. Commodore Ben Wyatt, the U.S. naval commander of the Marshall Islands, ordered the evacuation of “10 Red Cross workers, 19 USO women, 17 native women, 16 male [hospital] patients, four tiny babies, one small boy, and two navy doctors,” to the USS Rockbridge, which then steamed in deep water off the atoll until the danger passed. One of the Red Cross workers, Reva Hurwitz, played bridge in the ship’s wardroom until 2 a.m., a luxury since the island curfew, strictly enforced, was 10:30 pm. The tsunami bypassed Kwajalein, and everyone returned to the island less than twenty-four hours after being evacuated. Although the evacuation proved unnecessary, the women were grateful, said Hurwitz, because they had the opportunity “to use hot water and eat fresh fruit.”

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Thermodynamic analysis of a two-stage binary-fluid ejector heat pump water heater

Ejector heat pump water heaters (EHPWHs) could significantly increase the thermal efficiency of domestic water heating and reduce greenhouse gas emissions. This study addresses two major technical barriers to using EHPWHs in domestic water heating—low heating cycle coefficient of performance (COP) and low condensation temperatures—using binary fluid pairs as a working fluid in a two-stage ejector system. A comprehensive, geometry-free model of binary-fluid ejectors was built and validated to predict the entrainment ratios of binary-fluid ejectors. A thermodynamic model of a two-stage binary-fluid ejector EHPWH was built to predict the heating cycle COP of EHPWHs. The performance of the EHPWH was theoretically evaluated using HFE7000 and Novec649 as primary fluids and R600 and R1234ze(Z) as secondary fluids. HFE7000/R600 gave the highest heating cycle COP (i.e., 1.356) in producing domestic hot water at 60.0 °C. An optimum evaporation temperature of the primary fluid was identified for the maximum effective entrainment ratio and effective pressure lift ratio of two-stage ejectors. Here, the effective entrainment ratio of the two-stage ejector dominated the heating cycle COP of the EHPWH. Primary fluids with lower latent heats of evaporation and/or secondary fluids with higher latent heats of evaporation yielded higher heating cycle COPs of EHPWHs.

42 ENGINEERING↗
DOE OSTI2023

Field Performance of R-1234yf Heat Pump Water Heaters

Heat pump water heaters (HPWH) provide a resource for increasing water heating efficiency in U.S. residences. Electric HPWHs have traditionally utilized R-134a as the refrigerant in the vapor-compression cycle; however, this refrigerant is undesirable long-term due to its high global warming potential. For HPWHs, low global warming potential refrigerants such as R-1234yf may offer comparable performance, but the evaluation of these systems has been limited to laboratory settings. This study provides field evaluations of off-the-shelf HPWHs that had their factory R-134a refrigerant replaced with an optimized charge of R-1234yf. The field evaluation consisted of R-1234yf HPWHs at two occupied field sites and two unoccupied, simulated lab homes. At the two residential field sites with occupants, the R-1234yf HPWHs operated issue-free for the 18-month field trial, and the home occupants perceived no change in HPWH performance relative to their prior R-134a HPWHs. At the lab homes, under simulated hot water draws, the average daily operating efficiency of the R-1234yf HPWH was within 2% of the baseline R-134a HPWHs.

42 ENGINEERING↗
DOE OSTI2022

Detailed Laboratory Evaluation of Electric Demand Load Shifting Potential of Controlled Heat Pump Water Heaters

The demand profile management of electric end uses is vital research for utilities and policymakers planning greenhouse gas emission reductions. In this study, detailed laboratory research was conducted on the load shifting potential of 4 grid-connected HPWHs and one electric resistance water heaters (ERWH). The testing applied different CTA-2045 shed and critical peak command designs under three water draw profiles. Highly-controlled laboratory experiments were conducted in Florida. One of the four HPWHs was a prototype incorporating the new CTA-2045-B protocol feature allowing ‘advanced’ load-up above tank setpoint. A three-hour morning (6 – 9 AM) and four-hour evening curtailment (4 – 8 PM) were defined as the shed or critical peak periods reflecting high-value control periods for utility coincident load for system-wide electric demand reductions. Tests were performed under baseline conditions (no load shift) and under varied load-shifting schemes, including load up and advanced load up, ahead of shed and critical peak commands. Data were collected from December 2020 – February 2022 in the laboratory and compared with field experiments in Florida and the Pacific Northwest. Grid-connected HPWHs were found to reduce peak demand by up to 0.47 kW compared to uncontrolled HPWH units, depending on time of day, control scheme, draw profile, and temperature cluster. The load up strategy demonstrated the ability of all units to utilize heat pump mode for extended periods ahead of peak events. Demand reductions for the HPWHs were much larger when compared with the ERWH— up to 1.64 kW with large hot water draws in winter.

Fenaughty, Karen↗
DOE OSTI2026

COGIHTO: Comprehensive Geothermal Integrated HVAC Retrofits in Disadvantaged Communities

Geothermal heating and cooling (GHC) systems offer one of the most efficient approaches to provide space conditioning and water heating in buildings. Due to the relatively stable temperature of the ground year-round, these systems can provide an efficient solution to decarbonize heating systems. Yet this technology has faced limited market adoption due to its high first cost. This project seeks to address this barrier by designing a community GHC system at a public housing development in New York, taking advantage of load diversity (in terms of the timing and amount of heating / cooling used per person) that a larger community offers to reduce the size and thus first cost of a GHC system. Project success would result in societal benefit from reduced energy and fossil fuel use, reduced local emissions, and improved comfort, which would positively impact the health and well-being this community. This report presents the findings from Phase 1 project supported by the Department of Energy’s Geothermal Technologies Office and includes the technical design of a GHC at a public housing development in New York. To support the success of a potential deployment of a GHC system, the team conducted community engagement and prepared an assessment of the local workforce needs. The project team, led by EPRI, considered a subset of NYCHA housing developments that were previously identified by NYCHA as suitable for GHC retrofits. This report presents the site selection criteria the team developed and the overall score assigned to each of the eight developments considered. One site was selected for focus of the technical design: Stapleton Houses in Staten Island, a mid-size development with roughly 700 apartments across 6 buildings. The site has an existing hot water hydronic loop served by natural gas boilers for space heating and water heating. The technical design partner assessed baseline energy consumption at the site and established thermal models of the apartment buildings to assist in the design. The team considered several GHC system configurations and selected a hybrid geothermal design fed from water-source heat pumps with auxiliary gas boilers in a central plant. This design best leveraged the existing site configuration and minimized costs due to additional electrical infrastructure upgrades. The report also details the feedback received from community engagement efforts and the findings from the workforce needs assessment and workforce transition plan. Members of the site maintenance staff and the resident advisory council were interviewed for their input and feedback about both the site’s existing heating/cooling infrastructure and how a construction project would impact resident life. This feedback was taken into consideration when completing the geothermal system design. Research was conducted into existing workforce development opportunities available to NYCHA residents. A workforce development plan was established using information from NYCHA’s resident economic empowerment and sustainability group, along with training material and curriculum from the International Ground Source Heat Pump Association (IGSHPA).

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Effect of using a nitrogen atmosphere on enzyme hydrolysis at high corn stover loadings in an agitated reactor

A comprehensive review of the literature shows that enzyme hydrolysis efficiency decreases with increased solids loadings at constant enzyme:cellulose ratios for pretreated lignocellulosic substrates. In seeking a mechanistic explanation for this phenomenon, we found that a nitrogen atmosphere enhances enzyme hydrolysis and minimizes the decrease in glucose yields as solids loadings are increased in an agitated bioreactor. Further, for liquid hot water pretreated corn stover, at solids loadings of both 100 and 200 g/L and hydrolyzed for 72 hr in a 1 L bioreactor at pH 5.0 with 3.6 mg protein per g biomass, glucose yields were 55% in a nitrogen atmosphere versus 45% in air with agitation and about 34% without agitation. While mixing promotes biomass/enzyme contact and disperses sugars released during hydrolysis that would otherwise cause product inhibition, nitrogen gas displaces air, avoiding deactivation of cellulases by oxygen. The nitrogen effect points to a facile approach of enhancing hydrolysis at high solids loadings.

09 BIOMASS FUELS↗
DOE OSTI2022

Structural characterization and biological activity of an α-glucan from the mollusk Marcia hiantina (Lamarck, 1818)

Marcia hiantina (Mollusca, Bivalvia) (Lamarck, 1818), is an edible clam mainly distributed along the tropical coastal regions. Recent researches have demonstrated that clams can possess compounds, including polysaccharides, with a wide range of biological actions including antioxidant, immunomodulatory and antitumor activities. Here an α-glucan was isolated from M. hiantina by hot water, purified by anion exchange chromatography, and its structure was characterized by a combination of multiple nuclear magnetic resonance (NMR) methods (1D 1 H, 1 H- 1 H COSY, 1 H- 1 H TOCSY, 1 H- 1 H NOESY, 1 H- 13 C HSQC and 1 H- 13 C HSQC-NOESY spectra), gas chromatography-mass spectrometry, and high performance size exclusion chromatography (HPSEC). The analysis from NMR, monosaccharide composition, methylation analyses and HPSEC combined with multi angle light scattering (MALS) of M. hiantina-derived α-glycan confirmed a branched polysaccharide exclusively composed of glucose (Glc), mostly 4-linked in its backbone, branched occasionally at 6-positions, and having a molecular weight of ~ 570 kDa. The mollusk α-glucan was subjected to four cell-based assays: (i) viability of three cell lines (RAW264.7, HaCaT, and HT-29), (ii) activity on lipopolysaccharide (LPS)-induced prostaglandin production in RAW264.7 cells, (iii) inhibitory activities of in H 2 O 2 - and LPS-induced reactive oxygen species (ROS) production in HMC3 cells, and (iv) HaCaT cell proliferation. Furthermore, results have indicated no cytotoxicity, potent inhibition of both H 2 O 2 - and LPS-induced ROS, and potent cell proliferative activity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Understanding the Effects of Ash Content on Various Pretreatment Technologies for the Bioconversion of Corn Stover

Here, the study aimed to examine the effects of adding biomass ash on the biochemical processes involved in fermentable sugar production. Corn stover was pretreated using several methods—hot water, dilute acid, alkaline, γ-valerolactone, and ionic liquid methods, each examined with ash loadings of 7.18% and 21.07%. The findings demonstrated that increased ash content adversely affected both pretreatment and enzymatic hydrolysis. Specifically, the total sugar yield was 3 to 16% lower at the higher ash content across all pretreatment methods, and up to 4.01% lower during enzymatic hydrolysis. For acidic pretreatment, the sugar yield decreased as ash content increased. In contrast, ash content had a lesser impact on alkaline pretreatment compared to acidic pretreatment. For example, using corn stover with an ash content as high as 22.65% resulted in only a 2.90% decrease in total sugar yield compared to corn stover without added ash. Further, the primary reasons for the reduced sugar yield in higher ash biomass during acidic pretreatments were likely the neutralizing effect of the ash and decreased acid access to the substrates. During enzymatic hydrolysis, ash reduced the sugar yield by limiting enzyme access to cellulose.

09 BIOMASS FUELS↗
DOE OSTI2022

Application and evaluation of a pattern-based building energy model calibration method using public building datasets

Building performance simulation has been adopted to support decision making in the building life cycle. An essential issue is to ensure a building energy simulation model can capture the reality and complexity of buildings and their systems in both the static characteristics and dynamic operations. Building energy model calibration is a technique that takes various types of measured performance data (e.g., energy use) and tunes key model parameters to match the simulated results with the actual measurements. This study performed an application and evaluation of an automated pattern-based calibration method on commercial building models that were generated based on characteristics of real buildings. A public building dataset that includes high-level building attributes (e.g., building type, vintage, total floor area, number of stories, zip code) of 111 buildings in San Francisco, California, USA, was used to generate building models in EnergyPlus. Monthly level energy use calibrations were then conducted by comparing building model results against the actual buildings' monthly electricity and natural gas consumption. The results showed 57 out of 111 buildings were successfully calibrated against actual buildings, while the remaining buildings showed opportunities for future calibration improvements. Enhancements to the pattern-based model calibration method are identified to expand its use for: (1) central heating, ventilation and air conditioning (HVAC) systems with chillers, (2) space heating and hot water heating with electricity sources, (3) mixed-use building types, and (4) partially occupied buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Benchtop assessment of sealing efficacy and breathability of additively manufactured (AM) face masks

The onset of the 2019 novel coronavirus disease (COVID-19) led to a shortage of personal protective equipment (PPE), medical devices, and other medical supplies causing many stakeholders and the general public alike to turn to additive manufacturing (AM) as a stopgap when normally accessible devices were not available. However, without a method to test these AM constructs, there continued to be a disconnect between AM suppliers and the community’s needs. The objective of this study was to characterize the pressure drop and leakage of four different publicly available AM face mask models with two filter material combinations, as well as to investigate the impact of frame modification techniques including the use of foam strips and hot-water face forming to improve fit when the masks are donned on manikin head forms. AM face mask frame designs were downloaded from public repositories during the early stages of the COVID-19 pandemic. AM face masks were fabricated and tested on manikin head forms within a custom chamber containing dry aerosolized NaCl. Pressure drops, particle penetration, and leakage were evaluated for various flow rates and NaCl concentrations. Results indicated that filter material combination and frame modification played a major role in the overall performance of the AM face masks studied. Filter material combinations showed improved performance when high filtration fabric was used, and the cross-sectional area of the fabric was increased. AM frame modifications appeared to improve AM face mask leakage performance by as much as 69.6%.

36 MATERIALS SCIENCE↗