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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 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Water effects on NH 3 -SCR over Cu-based small-pore zeolite catalysts: A review

The selective catalytic reduction (SCR) of NO x with NH 3 as the reductant over small-pore Cu-zeolite catalysts is a leading strategy for controlling emissions from diesel engines and mobile sources. While the hydrothermal stability of Cu-zeolites such as Cu-SSZ-13, Cu-SAPO-34, and Cu-SSZ-39 has been extensively studied, the multifaceted role of water vapor under operating conditions has only recently received systematic attention. Water impacts multiple aspects of SCR catalysis, including NO x conversion, N 2 O formation, Cu ion speciation, redox kinetics, and surface reactions. This review comprehensively summarizes recent advances in understanding the effect of water on NH 3 -SCR over Cu-based catalysts. For Cu-SSZ-13, water vapor induces both inhibitory and promotive effects depending on temperature, Cu loading, and Si/Al ratio by altering NH 3 adsorption, Cu mobility, and redox half-cycle kinetics. Studies have revealed that water can suppress ammonium nitrate formation at low temperatures and enhance nitrate pathways at higher temperatures. Over Cu-SAPO-34, water promotes NO conversion by improving Cu(II) reducibility and strengthening Brønsted acidity. First-principles calculations confirm that water-coordinated Cu species lower O 2 activation barriers. In Cu-SSZ-39, water was found to facilitate Cu reduction, migration, and O 2 activation, resulting in superior water tolerance and unexpected catalytic promotion. Both experimental and computational studies highlight that water vapor exerts complex, catalyst-dependent effects on NH 3 -SCR performance, underscoring the need for tailored catalyst designs that leverage beneficial water interactions while minimizing inhibitory impacts.

Ammonia selective catalytic reduction↗
DOE OSTI2017

Single-unit-cell layer established Bi 2 WO 6 3D hierarchical architectures: Efficient adsorption, photocatalysis and dye-sensitized photoelectrochemical performance

Single-layer catalysis sparks huge interests and gains widespread attention owing to its high activity. Simultaneously, three-dimensional (3D) hierarchical structure can afford large surface area and abundant reactive sites, contributing to high efficiency. Herein, we report an absorbing single-unit-cell layer established Bi2WO6 3D hierarchical architecture fabricated by a sodium dodecyl benzene sulfonate (SDBS)-assisted assembled strategy. The DBS- long chains can adsorb on the (Bi2O2)2+ layers and hence impede stacking of the layers, resulting in the single-unit-cell layer. We also uncovered that SDS with a shorter chain is less effective than SDBS. Due to the sufficient exposure of surface O atoms, single-unit-cell layer 3D Bi2WO6 shows strong selectivity for adsorption on multiform organic dyes with different charges. Remarkably, the single-unit-cell layer 3D Bi2WO6 casts profoundly enhanced photodegradation activity and especially a superior photocatalytic H2 evolution rate, which is 14-fold increase in contrast to the bulk Bi2WO6. Systematic photoelectrochemical characterizations disclose that the substantially elevated carrier density and charge separation efficiency take responsibility for the strengthened photocatalytic performance. Additionally, the possibility of single-unit-cell layer 3D Bi2WO6 as dye-sensitized solar cells (DSSC) has also been attempted and it was manifested to be a promising dye-sensitized photoanode for oxygen evolution reaction (ORR). Our work not only furnish an insight into designing single-layer assembled 3D hierarchical architecture, but also offer a multi-functional material for environmental and energy applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Alkali-metal poisoning effect of total CO and propane oxidation over Co 3 O 4 nanocatalysts

Cobalt oxide (Co 3 O 4 ), a low-cost transitional metal oxide, has been widely studied for catalytic total oxidation of CO and hydrocarbons. However, much less attention has been paid to the poisoning effect due to alkali metals in such oxidation catalysts despite the ease of access to such poisons in both mobile and stationary combustion sources. Here, the alkali metals such as Na, K and Li were readily deposited onto a Co 3 O 4 catalyst to study their poisoning effect on CO and propane oxidation. 1% doping onto Co 3 O 4 was found to increase the light-off temperature by 50 ºC in CO oxidation and over 160 ºC in propane oxidation. It is also noted that alkali metals exhibited a 'locking-effect' on oxygen of Co 3 O 4 , leading to poor oxygen mobility of alkali metal doped catalysts. Lastly, during the reaction, alkali metals can significantly promote the adsorption of CO 2 to form robust surface carbonate species even at high temperature, another reason for the poisoning effect of alkali metals on Co 3 O 4 nanocatalysts for catalytic oxidation.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Enhanced visible-light-assisted peroxymonosulfate activation on cobalt-doped mesoporous iron oxide for orange II degradation

Sulfate radical-based advanced oxidation processes (SR-AOP) attracted a lot of attention due to their capability and adaptability in wastewater treatment. Although heterogeneous cobalt-based catalysts have been extensively studied and have emerged superior for peroxymonosulfate (PMS) activation, leaching of cobalt is still a major concern. Herein, we report a photo-assisted PMS activation approach using cobalt doped mesoporous iron oxide with exceptional activity and stability up to 7 cycles with very low cobalt leaching (0.5 ppm). The highest activity was obtained by 1 mol % cobalt doped mesoporous iron oxide. Orange II dye was completely degraded by the reactive oxygen species (ROS) generated under visible light irradiation within 1 min. ROS were evaluated using two distinct techniques (Fluorescence probes and Electron Paramagnetic Resonance (EPR). ROS quenching experiments were also used to highlight the dominant pathway. This study correlates the structural and electronic changes induced with cobalt doping to the exceptional activity.

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

Investigation of NO adsorption and desorption phenomena on a Pd/ZSM-5 passive NO x adsorber

Pd-based zeolite materials have gained significant attention as passive NO x adsorbers (PNAs) for diesel-engine cold-start NO x mitigation due to their ability to store NO x at low temperatures. Pd/ZSM-5 is a promising PNA candidate, however, the NO adsorption mechanism over this material is not well understood. This study combines flow reactor experiments and surface spectroscopy to investigate NO adsorption under a variety of conditions. Furthermore, the state of hydration of the Pd cations played an important role in determining the impact of H 2 O and CO concentration on the PNA performance. Below 150 °C, the inhibition effect of H 2 O on NO adsorption was mitigated by CO. Due to dehydration, neither H 2 O nor CO had an impact on NO uptake at 150 °C, where maximum NO storage capacity of the PNA was also observed. The observed gas composition and temperature effects on NO adsorption and formation of surface intermediates ultimately inform a proposed mechanism.

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

General volume sizing strategy for thermal storage system using phase change material for concentrated solar thermal power plant

With an auxiliary large capacity thermal storage using phase change material (PCM), Concentrated Solar Power (CSP) is a promising technology for high efficiency solar energy utilization. In a thermal storage system, a dual-media thermal storage tank is typically adopted in industry for the purpose of reducing the use of the heat transfer fluid (HTF) which is usually expensive. While the sensible heat storage system (SHSS) has been well studied, a dual-media latent heat storage system (LHSS) still needs more attention and study. The volume sizing of the thermal storage tank, considering daily cyclic operations, is of particular significance. In this paper, a general volume sizing strategy for LHSS is proposed, based on an enthalpy-based 1D transient model. One example was presented to demonstrate how to apply this strategy to obtain an actual storage tank volume. With this volume, a LHSS can supply heat to a thermal power plant with the HTF at temperatures above a cutoff point during a desired 6 hours of operation. This general volume sizing strategy is believed to be of particular interest for the solar thermal power industry.

14 SOLAR ENERGY↗
DOE OSTI2017

Numerical modeling study of a man-made low-permeability barrier for the compressed air energy storage in high-permeability aquifers

Compressed air energy storage (CAES) is a grid-scale energy storage technology for intermittent energy, as proven by the decades-long successful operation of two existing compressed air energy storage in cavern (CAESC) power plants. Because of the limited availability of salt domes appropriate for CAESC, the more widely available aquifers (compressed air energy storage in aquifers, CAESA) have recently attracted considerable attention as candidates for CAES. An ideal aquifer for CAESA is highly permeable around the well to facilitate easy injection and withdrawal of air, but the high-permeability region is surrounded by low-permeability zones to minimize the loss of injected air and decrease in energy efficiency. However, such ideal geological structures are not always available in nature. Therefore, the potential of creating man-made low-permeability barrier in high-permeability aquifers is very interesting. In this paper, we investigate the feasibility of man-made low-permeability barriers in high-permeability aquifers using the numerical simulator TOUGH2/Gel to calculate the three-component flow (including a miscible gelling liquid). The simulation results show that an expected low-permeability barrier can be created by injecting grout with certain properties, and the altered aquifer performs well for CAESA. Additional sensitivity studies are also performed to reveal the effects of the various factors on the success of the low-permeability barrier creation, including the critical solidification concentration, the scale factor of the time dependence of the grout viscosity, the relative density of the grout, and the volume of the follow-up water injection. The results indicate that, in a horizontal aquifer, low critical solidification concentrations, and small scale factors are generally preferred and the density of grout should be close to that of the in situ water. For the given volume of the injected grout, there is an optimal follow-up water injection that will create the largest storage space without damaging the barrier. Furthermore, these results may help to extend the candidate sites for CAESA and the prospect of large scale energy storage.

25 ENERGY STORAGE↗
DOE OSTI2018

Impacts of building geometry modeling methods on the simulation results of urban building energy models

We present that urban-scale building energy modeling (UBEM)—using building modeling to understand how a group of buildings will perform together—is attracting increasing attention in the energy modeling field. Unlike modeling a single building, which will use detailed information, UBEM generally uses existing building stock data consisting of high-level building information. This study evaluated the impacts of three zoning methods and the use of floor multipliers on the simulated energy use of 940 office and retail buildings in three climate zones using City Building Energy Saver. The first zoning method, OneZone, creates one thermal zone per floor using the target building's footprint. The second zoning method, AutoZone, splits the building's footprint into perimeter and core zones. A novel, pixel-based automatic zoning algorithm is developed for the AutoZone method. The third zoning method, Prototype, uses the U.S. Department of Energy's reference building prototype shapes. Results show that simulated source energy use of buildings with the floor multiplier are marginally higher by up to 2.6% than those modeling each floor explicitly, which take two to three times longer to run. Compared with the AutoZone method, the OneZone method results in decreased thermal loads and less equipment capacities: 15.2% smaller fan capacity, 11.1% smaller cooling capacity, 11.0% smaller heating capacity, 16.9% less heating loads, and 7.5% less cooling loads. Source energy use differences range from -7.6% to 5.1%. When comparing the Prototype method with the AutoZone method, source energy use differences range from -12.1% to 19.0%, and larger ranges of differences are found for the thermal loads and equipment capacities. This study demonstrated that zoning methods have a significant impact on the simulated energy use of UBEM. Finally, one recommendation resulting from this study is to use the AutoZone method with floor multiplier to obtain accurate results while balancing the simulation run time for UBEM.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

A generic microgrid controller: Concept, testing, and insights

Microgrids have garnered attention in recent years as a way to increase the reliability of the grid, increase the reliability of electricity service to customers, adapt to an increasing percentage of intermittent renewable generation, and serve both customer critical loads and the needs of adjacent communities in the case of emergencies such as natural disasters. One barrier to microgrids is the historic cost and lack of standardization associated with microgrid controllers. To reduce this cost and address standardization, specifications for a Generic Microgrid Controller (GMC) were developed with the goal to facilitate the design and ease of adaptation of microgrid controllers to various microgrids of different sizes and with different resources. A GMC must address two core functions, Transition and Dispatch, as well as several optional higher level functions such as economic dispatch, and renewable and load forecasting. The GMC specifications were demonstrated and evaluated using a commercial simulation platform for two different microgrids, a 20MW-Class community microgrid and a 10MW-Class medical center microgrid. For each microgrid, the GMC was tested in hardware-in-the-loop (HIL) using an OPAL-RT real-time digital simulator, and the two core functions were assessed. The results established that (1) the GMC is successful in seamlessly transitioning the microgrids to and from an islanded mode, (2) a load/generation mismatch at the time of separation depends on the microgrid configuration and must be lower than a specific value determined by simulation testing, and (3) the GMC Dispatch Function response is acceptable in maintaining, in the islanded mode, 60Hz for a range of load changes.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Practical factors of envelope model setup and their effects on the performance of model predictive control for building heating, ventilating, and air conditioning systems

Model predictive control (MPC) for buildings is attracting significant attention in research and industry due to its potential to address a number of challenges facing the building industry, including energy cost reduction, grid integration, and occupant connectivity. However, the strategy has not yet been implemented at any scale, largely due to the significant effort required to configure and calibrate the model used in the MPC controller. While many studies have focused on methods to expedite model configuration and improve model accuracy, few have studied the impact a wide range of factors have on the accuracy of the resulting model. In addition, few have continued on to analyze these factors’ impact on MPC controller performance in terms of final operating costs. Therefore, this study first identifies the practical factors affecting model setup, specifically focusing on the thermal envelope. The seven that are identified are building design, model structure, model order, data set, data quality, identification algorithm and initial guesses, and software tool-chain. Then, through a large number of trials, it analyzes each factor's influence on model accuracy, focusing on grey-box models for a single zone building envelope. Finally, this study implements a subset of the models identified with these factor variations in heating, ventilating, and air conditioning MPC controllers, and tests them in simulation of a representative case that aims to optimally cool a single-zone building with time-varying electricity prices. It is found that a difference of up to 20%25 in cooling cost for the cases studied can occur between the best performing model and the worst performing model. The primary factors attributing to this were model structure and initial parameter guesses during parameter estimation of the model.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Forecasting district-scale energy dynamics through integrating building network and long short-term memory learning algorithm

With the development of data-driven techniques, building energy prediction on a district level has attracted increasing attention in recent years for revealing energy use patterns and reduction potentials. However, data acquisition in large building groups is difficult and adjacent buildings also interact with each other. To reduce data cost and incorporate the inter-building impact with the data-driven building energy model, this study proposes a deep learning predictive approach that fuses the building network model with a long short-term memory learning model for district-scale building energy modeling. The building network was constructed based on correlations between the energy use intensity of buildings, which can significantly reduce the computational complexity of the deep learning models for energy dynamic prediction. Five typical building groups with energy use data from 2015 to 2018 on two institutional campuses were selected to perform the validation experiment with TensorFlow. Based on the prediction error assessments, the results suggest that for total building energy use intensity prediction, the proposed model can achieve a mean absolute percentage error of 6.66% and a root mean square error of 0.36 kWh/m 2 , compared to 12.05% and 0.63 kWh/m 2 of the conventional artificial neural network model and to 11.06% and 0.89 kWh/m 2 for the support vector regression model.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Automatic and rapid calibration of urban building energy models by learning from energy performance database

Urban building energy modeling (UBEM) is attracting increasing attention in the energy modeling filed. Unlike modeling a single building using detailed building systems information, UBEM generally uses limited high-level building stock data to infer default assumptions about building characteristics and operations. Additionally, this practice inherently brings uncertainty to UBEM. This study introduced a novel method of automatic and rapid calibration of UBEM based on the annual electricity and natural gas energy use data by learning the correlations between crucial model input parameters and the building energy use from the reference building models. A case study was presented to calibrate 72 large office buildings built before 1978 in San Francisco. Seventeen model parameters were selected and Monte Carlo sampling was used to create 1000 samples that reasonably represent the parameter space. Then 1000 simulations were performed for the reference building model to create an energy performance database. The results showed that by learning from the energy performance database, it took less than four simulation runs on average to calibrate a building model. After the calibration, the distributions of each parameter were obtained to replace their single predefined default values. For example, the default lighting power density of 21.39 W/m 2 was calibrated to be 7.50 W/m 2 on average. The case study successfully demonstrated the effectiveness of the novel calibration method for UBEM in the mild climate. The method will be further tested in future for other climate zones and other building types.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Nationwide HVAC Energy-Saving Potential Quantification for Office Buildings with Occupant-Centric Controls in Various Climates

The occupant-centric control (OCC) is receiving an increasing attention due to its ability to reduce building heating ventilation and air-conditioning (HVAC) system energy consumptions while not affecting the occupant thermal comfort. This paper aims to investigate and quantify the nationwide energy-saving potential of implementing the occupant-centric HVAC controls in typical office buildings using a whole building simulation software EnergyPlus. First, the medium office and large office from the Department of Energy (DOE) Commercial Prototype Building Models (CBPM) were enhanced to have detailed layouts and dynamic occupancy schedules. Then, a comprehensive simulation plan was created by incorporating the multiple zone-level and system-level occupant-centric building HVAC controls recommended by the updated ASHRAE Standard 90.1 – 2019 and ASHRAE Guideline 36 – 2018. Three control scenarios with different occupancy sensing methods were identified in this simulation plan. A nation-wide parametric analysis which includes two building types, three occupancy sensing scenarios, two building code versions, and 16 U.S. climate zones was carried out. The simulation results of the key control variables and HVAC energy consumption suggest that generally, both the occupancy presence sensor and occupant counting sensor could achieve energy savings for the office buildings in majority of the scenarios. However, compared with the occupancy presence sensor, which could support both the temperature setpoint reset and operational breathing zone airflow rate reset for the unoccupied zones, the occupant counting sensor only brings a marginal benefit. Besides, a higher HVAC energy-saving ratio could be achieved in the heating-dominated zone, since the energy reduction brought with the minimum outdoor airflow rate reset is stronger in the heating mode.

Pang, Zhihong↗
DOE OSTI2020

A comparison study on trading behavior and profit distribution in local energy transaction games

With the increasing integration of distributed energy resources, localized peer-to-peer energy transactions are receiving more attention since they could absorb more distributed renewables locally and stabilize the power grid. To better study the trading behavior and provide guidance for a viable local market design, different game-theoretical frameworks including cooperative and non-cooperative games are established and compared here. For the cooperative grand coalition, the maximum social welfare is guaranteed, the Shapley value and bargaining based approaches are implemented for further profit redistribution. It is shown that the asymmetrical bargaining power can be critical in the final payment clearing and it is equivalent to the Shapley value allocation if prosumers bargain based on their marginal contributions. Non-cooperative trading is formulated by using a Stackelberg bilevel model in which the upper level has the privilege in internal price setting. However, system optimum is not obtained due to competition, and the selfish leader could take away 89% of the collective benefit by price-gap based arbitraging. Aiming for a long-lasting trading market, a virtual benevolent leader and a uniform price structure in which purchase price equals selling price are tested. Experimental results indicate that maximum social welfare and a fairer profit allocation can be achieved with a uniform price structure, regardless of the selfish or benevolent attitude.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Simulation-based Performance Evaluation of Model Predictive Control for Building Energy Systems

The performance of model predictive control (MPC) can be significantly affected by different choices of controller parameters such as the time intervals for model discretization and control sampling. Due to the lack of a systematic understanding on how these parameters affect control performance, they are usually selected arbitrarily in practice.In this paper, the combined impacts of selected time intervals for model discretization and control sampling on the performance of MPC are comprehensively investigated for the first time through detailed simulations. Specifically, a typical MPC strategy is first designed to improve building operations based on a reduced-order model of building dynamics. Then, the performance of the designed MPC is evaluated against different choices of time intervals for model discretization and control sampling on a simulated office building. The detailed simulation results reveal that the time interval for model discretization has a much greater influence on the performance of MPC than the time interval for control sampling. Although the time interval for control sampling usually receives more attentions in practice, it turns out that the time interval for model discretization affects the prediction performance, cost saving, and computation time simultaneously and more significantly. Therefore, the simulation-based performance evaluation presented here sheds light on the impacts of different time intervals and facilitates their selection for practical applications of MPC to building operations

Huang, Sen↗
DOE OSTI2021

Extended convex hull-based distributed optimal energy flow of integrated electricity-gas systems

Integrated electricity and gas systems are constructed to facilitate the gas-fired generation, and the distributed operation of these integrated systems have received much attention due to the increased emphasis on data security and privacy between different agencies. This paper proposes an extended convex hull based method to address optimal energy flow problems for the integrated electricity and gas systems in a distributed manner. First, a multi-block electricity-gas system model is constructed by dividing the whole system into N blocks considering both physical and regional differences. This multi-block model is then convexified by replacing the nonconvex gas transmission equation with the extended convex hull-based constraints. The Jacobi-Proximal alternating direction method of multipliers algorithm is adopted to solve the convexified model and minimize its operation cost. Finally, the feasibility of the optimal solution for the convexified model is checked, and a sufficient condition is developed. If the sufficient condition is satisfied, the optimal solution for the original nonconvex problem can be recovered from that for the convexified problem. Simulation results demonstrate that the proposed method is tractable and effective in obtaining feasible optimal solutions for multi-block optimal energy flow problems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Optimising the geospatial configuration of a future lithium ion battery recycling industry in the transition to electric vehicles and a circular economy

Rapid electrification of the transport system will generate substantial volumes of Lithium-ion-battery (LiB) waste as batteries reach their end-of-life. Much attention focuses on the recycling processes, neglecting a broader systemic view that considers the concentration of the costs and impacts associated with logistics and transportation. This paper provides an economic, environmental and geospatial analysis of a future LiB recycling industry in the UK. Hitherto, state-of-the-art assessment methods have evaluated life cycle impacts and costs but have not considered the geographical layer of the problem. This paper develops a GSC derived supply chain model for the UK electric vehicle and end-of-life vehicle battery industry. Considering both pyrometallurgical and hydrometallurgical recycling technologies, the optimisation process takes into account anticipated EV volumes, and, based on anticipated near-term technological evolution of LiBs, the evolution of the mix of battery cathodes in production, and presents a number of scenarios to show where LiB recycling facilities should ideally be geographically located. An economic and environmental assessment based on a customised EverBatt model is provided.

25 ENERGY STORAGE↗
DOE OSTI2022

The importance of maldistribution matching for thermal performance of compact heat exchangers

Compact heat exchangers have gained increased attention in recent years, particularly in demanding applications where high temperatures, high pressures, and/or high power densities are required. For decades, the heat exchanger (HX) community believes that flow maldistribution is a key factor for HX effectiveness, that is, reducing the degree of flow maldistribution (MALD) can help increase the HX effectiveness. Therefore, significant efforts have been devoted in the past to optimizing the header geometry to minimize flow maldistribution. This work was initially motivated by this, and the original goal was to figure out a HX header design with the lowest maldistribution. However, by systematically constructing a comprehensive maldistribution matrix, the analysis revealed that the HX effectiveness is not actually determined by the MALD, but instead dominated by the degree of maldistribution mismatch (MISM). This conclusion was also theoretically generalized, which indicated that matching of the local heat capacity rate is key for achieving maximum performance. The MISM provides a local means of tracking this information, while the MALD only provides a global approximation of the maldistribution itself. With this new perspective, flow maldistribution needs not necessarily be avoided, but instead matched between two fluid streams, to improve the HX performance. We demonstrated that by carefully designing the header geometry to match the velocity profiles of the two fluids in a 2 MW PCHE with molten salt and supercritical carbon dioxide (sCO2) as the heat transfer fluids, the HX could achieve a higher effectiveness even when the maldistribution increased. Finally, a technoeconomic study using a CSP system as an example revealed that the use of this new HX design paradigm could result in CSP capital cost savings as large as 16.6%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗