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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

DECENTRALIZED APPROACH TO MULTI-ZONE GREY-BOX MODELING FOR MODEL-BASED PREDICTIVE CONTROL

This study aims to improve the easiness of utilizing the grey-box model (i.e., Resistance-Capacitance circuit) for Model-based Predictive Control (MPC). The primary barrier of implementing the MPC is estimating the control-oriented building model that needs to be computationally inexpensive and quick but reasonably precise in predicting building load and indoor conditions. The estimating of the model parameters becomes more complicated when the building scale is larger; e.g., multi-zone building. In this study, a decentralized approach is introduced; each zone is split and individually estimated with measured boundary temperature from adjacent zones integrated into one single system model. The proposed decentralized method is demonstrated with experimental data from a full-scale multi-zone test cell compared with the centralized reference case.

Joe, Jaewan↗
DOE OSTI2020

Smart technologies enable homes to be efficient and interactive with the grid

Oak Ridge National Laboratory researchers compare two different approaches to test how advanced, energy-efficient building technologies such as smart thermostats, heat pump water heaters, and advanced heat pump HVAC (heating, ventilation and air conditioning) can be optimized within a home and connected at a neighborhood-scale load to a community microgrid in the Alabama Power Smart Neighborhood located in Hoover. Working with Southern Company and Alabama Power, ORNL researchers are pioneering that future where smart homes and smart neighborhoods can benefit both homeowners and utilities, by reducing energy consumption by 44% and peak demand by 34%.This project is one of two neighborhoods in the U.S Department of Energy’s (DOE’s) Connected Neighborhood project, supported by Building Technologies Office , where ORNL researchers leverages DOE investment in micro-grids and responsive, flexible building loads research to improve grid reliability – a goal of DOE’s Grid-interactive Efficient Buildings (GEB) Initiative. Researchers control the neighborhood and microgrid to enable utilities achieve their desired load and cost profiles while ensuring the comfort of homeowners in the Smart Neighborhood. This transactive control approach maximizes the utilization of technical resources of the microgrid and controllable loads, while reducing costs for both the homeowners and Alabama Power. These tests partially seek to determine a more precise range of tolerance with respect to occupant comfort as researchers work to facilitate customer acceptance and perception of new building technologies that enable energy savings.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Insights into the mechanisms of NH3 inhibition on Cu-CHA SCR catalysts

This work elucidates the atomic-scale mechanism behind ammonia (NH3) inhibition during the selective catalytic reduction (SCR) of NO? on Cu-CHA catalysts, a key issue limiting low-temperature emission control. Using SCR kinetic analysis, operando electron paramagnetic resonance (EPR) spectroscopy, and density functional theory (DFT), we demonstrate that NH3 inhibition primarily slows the oxidation half-cycle (OHC), while the reduction half-cycle (RHC) remains unaffected. DFT simulations reveal that excess NH3 substantially increases the diffusion barrier for CuI ions, hindering formation of essential CuII-oxo dimer intermediates and thus suppressing OHC kinetics. Operando EPR studies confirm that this inhibition strongly depends on operating temperature and catalyst Cu loading. Our findings highlight strategies to counteract NH3 inhibition, including optimizing Cu loading, precisely managing NH3:NO feed ratios, and enhancing CuI ion mobility through tailored catalyst design and operational adjustments, thereby advancing the efficiency of emission control technologies in automotive applications.

Deka, Dhruba Jyoti↗
DOE OSTI2019

Commercial Building Technology Demonstration (Final Scientific/Technical Report)

The background for this project was a unique and innovative concept that had been proposed and demonstrated by enVerid Systems, reducing the energy consumption in HVAC systems in commercial and public buildings by up to 50% at peak loads. The concept involves selective scrubbing of gas contaminants from indoor air as a practical substitute for outside air ventilation, the latter being the conventional practice today. This scrubbing enables recycling of most of the indoor air and significantly decreasing the amount of outside air, resulting in a reduced HVAC load and commensurate energy savings for the facility. Key to our approach is low cost scrubbing of all gas contaminants from indoor air using novel, efficient and regenerable sorbent materials. The total solution, labeled HLR (HVAC Load Reduction) is implemented by means of compact modules that can be retrofitted onto virtually any building, and utilizes novel sorbents that have been developed and brought to scale production by enVerid. Although the technology had been deployed and demonstrated, the US commercial building and HVAC markets, famously conservative with respect to innovation and new technologies, had yet to embrace the idea or the product. The overarching goal of the project was to help overcome market hesitancy and enable widespread adoption, by creating a critical mass of success stories across different regions and building types, all under oversight and verification of the DOE and NREL, to ensure credibility and accuracy. The project, overall, was a resounding success. Several installations were deployed and tested comprehensively for the impact on both energy consumption and indoor air quality, and results were not only excellent, but quantitatively in line with expectations. A total number of eight (8) installations were attempted, with 2 aborted due to building issues. Of the six successful installations, however, complete M&V was performed by NREL on 2 (Miami and NYC) and partial analysis on a third site (ArcBest), and these three, along with their results, were therefore presented from a financial and reporting standpoint. Although the number of case studies fell short of the original target of 10, we nevertheless had excellent demonstrations in vastly different climate zones: Southeast, Northeast and Midwest, and in very different building types. This included a modern high-rise office building in New York City and a University Campus health center in Miami, and a mid-rise high-density office in Arkansas. The cooling load reduction was shown to be significant, averaging 37% during the final cooling season in the Miami site. In the NYC site, the cooling energy savings were generally less, at around 12%, as expected. While this is a lower number for average/total savings, two comments are important to note: (i) the outside airflow (OA) reduction was not consistent during the data collection period, at least in part understating the attainable savings through incorrect measurement of the “high energy” reference state; and (ii) the peak impact in NYC is almost certainly as high as Miami, with critical ramifications for peak load reduction and equipment downsizing ability. Importantly, the measured energy savings in all locations were related to the outdoor climate conditions and the actual achievable reduction in outside air, very much in line with models and calculations; this leaves us with increased confidence in our understanding of the interaction between the technology and the building, and our ability to project the impact of this innovation in the future, through broad adoption. Simply put: the energy savings and load reduction impact of the HLR solution has been confirmed quantitatively. The results also confirmed the air quality objective. This may be even more significant, in that air quality is more complex and harder to measure and quantify, and the performance of the HLR as an air scrubber is the linchpin of the entire solution. In all sites, indoor air quality met or exceeded the required parameters, in terms of achieving the target (low) levels of indoor pollutants. Furthermore, the concentrations of outdoor sourced pollutants were markedly lower, as expected, mostly due to the reduction in outside air intake although in part also due to the scrubbing. The success was not immediate nor easy, and early challenges with the systems, especially (but not only) around controls and communication, caused delays in commissioning and undermined some of our M&V schedules. The good news is no fundamental issues were encountered and the number of such glitches was declining quickly by the end of the project. Other challenges had to do with coordinating the control of the building OA dampers, which the HLR needs to have in order to deliver the load reduction, but which the facility manager controls regularly and independently. This is not necessarily a problem for normal HLR operation but interferes with accurate M&V, where switching OA settings back and forth on a precise timetable is essential for clean data. The project provided valuable experience in retrofitting buildings that had been originally designed to operate with less recirculation and more outside air, and some key learnings related to the cyclical regeneration of the sorbents in the operational environment of the building. Some of these learnings gave already been incorporated into ongoing improvements in the design of the HLR module as well as the software that is used to control its operation. The cost and time of retrofit installations is much better understood; so is the test and balance procedure of the building that determines the available range of outside air reduction, which in turn determines the amount of load reduced. We had also implemented at least one annual cycle of sorbent cartridge replacement in the field, after which we tested the used sorbent to assess the rate of degradation of sorbent potency – an important factor affecting the long-term economics of HLR deployments. A notable shortfall of the project, other than the fact that the number of sites was below target, was that we had not (yet) completed testing to measure and verify (M&V) the winter energy savings. This is primarily due to late start on the NYC sites (Miami does not portend any heating savings associated with reduced outside air), combined with the issues of OA damper control. It is by no means suggested that such savings cannot be captured, only that the M&V with respect to winter in NYC has been incomplete. The value of this project and its interest to the general public are hard to overstate. The case studies created from Miami and especially from NYC have, without a doubt, opened up the interest of the broad HVAC industry to HLR in the past year. Major manufacturer reps have signed up to represent and promote the product, and dozens of top tier engineering consultants have introduced HLR as a base of design in upcoming construction and renovation projects – precisely the overarching goal of this project. These would not have happened without the highly visible installation in NYC and its ultimately satisfied customer. Furthermore, the DOE itself issued a report in late 2017 analyzing hundreds of candidate technologies for reducing energy consumption in HVAC; remarkably, the budding HLR solution ranked among the top 3(!); no doubt, its status as a viable and significant contender on this list is informed by the success of these demonstrations. And furthermore, in the wake of these demos, several major energy utilities, led by ConEdison in NYC, have endorsed the HLR solution and now routinely provide substantial cash rebates for customers choosing to incorporate the HLR in their buildings and reap the benefit of the reduced peak load as well as reduced cumulative energy demand. Last but not least, in January of 2019, as this report was being written, the HLR module won the AHR Expo Innovation Award for Green Buildings and, remarkably, the prestigious and only Product of the Year 2019, being selected by an independent professional panel of judges from AHR and ASHRAE. Given the confirmation of the enormous energy saving potential of HLR in widescale deployment, as well as ancillary but significant benefits in terms of equipment downsizing and indoor air quality, the benefit of this effort to the public speaks for itself. Accelerating adoption of HLR, without dependence on subsidies and driven by the private sector, is well under way. There is still much work to be done in terms of educating the HVAC and construction ecosystems and improving the product’s robustness and simplicity, to further facilitate the adoption of this technology and the capture of its potential value. But the American public will greatly benefit both directly and indirectly in the immediate future and beyond.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

A Self-Organizing Nano Grid (SONG) for Energy Access Clusters

In this paper, a bottom-up dc Self-Organizing Nano Grid (SONG) for rural electrification at ultra-low-cost through a flexible and scalable topology is presented. The proposed nano grid requires no communication and uses dc-bus signaling to convey excess energy in the system through the bus voltage, allowing independent agents to conduct energy transactions based on their needs in a decentralized manner. Moreover, this article proposes a concept that uses a novel multi-source, multi-segment droop control strategy with demand coordination, allowing for dynamic self-balancing of the system under fluctuating operating conditions. The unique use of a surplus photovoltaic (PV) power droop mode precisely estimates energy availability to minimize load chattering that helps in stabilizing the dc-bus. In addition, this architecture uses standard dc/dc converters for a low-cost, modular, Plug and Play ( PnP ) solution with highly automated operation, enabling local assembly, operation, and maintenance by non-technical personnel. The proposed SONG concept was validated in simulation and with a 700W, laboratory-scale, custom made nano grid system. The simulation and experimental test cases show the feasibility of the SONG system by demonstrating the proposed multi-source, multi-segment droop control strategy without load chattering under varying operating conditions.

dc-dc converter↗
DOE OSTI2025

A Neural Optimizer With Decision-Focused Learning for Optimal Energy Storage Operation

Here, this article introduces a neural optimizer-based framework for optimizing battery energy storage system (BESS) control for grid services, including demand charge and energy cost reduction. By leveraging decision-focused learning (DFL), the proposed framework ensures seamless integration and adaptation, significantly enhancing control performance. A patch time-series transformer is employed for peak load forecasting, incorporating aleatoric uncertainty quantification to account for forecasting uncertainties within the decision-making process. The framework utilizes a solver-in-the-loop approach to generate optimal BESS actions, which are then used to train the neural optimizer-based agent. By co-optimizing both BESS operational modes and output power within the NN, the system achieves improved performance and robustness. After initial training, the forecasting and control models are jointly fine-tuned to account for forecasting errors, further improving decision precision and efficiency through DFL. Case studies are performed to validate the performance of the framework using multiple real-world datasets, demonstrating superior performance in monthly peak load forecasting compared to state-of-the-art models. In addition, the results are compared against existing decision-making approaches. The results demonstrate a reduction in monthly peak forecasting error by approximately 15% across various performance measures and achieve an optimization gap for BESS operation that is about three times smaller compared to existing methods.

Kim, Hyeonjin [Pacific Northwest National Laborato↗
DOE OSTI2025

Multi-Agent Hierarchical Deep Reinforcement Learning for HVAC Control With Flexible DERs

As electricity consumption in commercial and residential buildings continues to rise, reducing energy costs presents an increasing challenge. Heating, ventilating, and air-conditioning (HVAC) systems, which typically account for 40%-50% of a building's energy use, are prime targets for energy savings. Intelligent control of HVAC temperature through the exploitation of HVAC load flexibility brings significant potential to reduce energy consumption and electricity expenses. The nonlinear models of HVAC systems challenge traditional control methods, while the uncertainty introduced by HVAC load flexibility complicates distributed energy resource (DER) management using conventional optimal dispatch techniques. In response to these challenges, we propose a hierarchical multi-agent deep reinforcement learning (DRL) approach. The lower-level agents focus on balancing comfort and energy conservation, while the upper-level DRL agents optimize the use of DERs to reduce peak demand based on the control outcomes of the HVAC by the lower-level agents. Here, in the upper-level agents, we incorporate a multi-agent structure based on ensemble learning, which acts based on historical and current data without relying on precise load forecasting to address the delayed rewarding issue in DRL. This allows for the effective reduction of energy costs. The proposed method is tested using a real-world microgrid comprising 413 buildings in Southern California, and the results demonstrate that our approach can significantly reduce overall electricity bills while ensuring the comfort of consumers and residents.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Iterative Linearization for Phasor-Defined Optimal Power Dispatch

Optimal power flow (OPF) problems, which dispatch power targets to controllable generating units across a network, must generally account for non-convex constraints on power flow. Furthermore, adapting those problems so as to make them solvable with convex optimization techniques is an area of much academic and operational interest. In this paper, we present a method for solving OPF as a quadratic program by iteratively refining and re-initializing a linearized model of power flow based on the outputs of an associated nonlinear solver. The linear model on which we demonstrate this method is an adapted version of an approximation designed for use with unbalanced distribution networks. As an important benefit, the model allows for the explicit inclusion of nodal voltage phasor values in both the OPF problem's objective and its constraints, which opens the door to the idea of phasor-based control (PBC) design. We show in simulations on the IEEE 13-node test feeder that our method quickly converges to a set of phasor targets that are sufficiently precise for use in operations at the distribution level.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Additive-Mixing Fuel Injection (AMFI): A device for robust control and improved performance of high-efficiency LTGC engines

Low-temperature gasoline combustion (LTGC) engines can provide high efficiencies with very low NOx and particulate emissions. Despite these major advantages, methods for controlling LTGC combustion timing, achieving robust autoignition, and good low-load performance have challenged the development of practical LTGC engines. A key reason is that the ideal reactivity of the fuel varies with operating conditions, with low-reactivity fuels working well at high loads and higher-reactivity fuels working better at low loads. This article introduces a new technique called Additive Mixing Fuel Injection (AMFI) that adjusts the reactivity of the gasoline to obtain good performance over the operating map. Moreover, AMFI can provide robust combustion-timing control because it precisely meters very small amounts (0.01–0.6 mm 3 ) of an ignition-enhancing additive into the fuel each engine cycle. The additive used was 2-ethylhexyl nitrate (EHN), a common, inexpensive diesel-fuel ignition improver, but other additives could be used. Because additive amounts are so small, a 2-gal reservoir would be sufficient for medium-duty applications with refilling only at service intervals of about 8000 mi. The AMFI system has been installed on a single-cylinder LTGC research engine and demonstrated to provide robust combustion-timing control over wide ranges of combustion phasing, fueling rate, intake boost, engine speed, and intake temperature. AMFI also increases the fuel’s reactivity sufficiently to greatly reduce or eliminate the need for charge heating, simplifying engine design and significantly increasing thermal efficiency and the maximum load at low-boost conditions. The nitrogen in the EHN produced a modest increase in NOx, but it was mitigated by lower intake temperatures, and NOx emissions remained very low. Finally, the additive increases the sensitivity of autoignition reactions to variations in the local fuel/air mixture within the charge. This allows the use of controlled fuel stratification for improved LTGC-engine performance, and its potential to improve low-load operation was demonstrated.

Dec, John E.↗
DOE OSTI2024

Understanding and Tailoring Diffusion and Co-Adsorption Inside the Confined Pores of Metal-Organic Frameworks (Final Scientific/Technical Report for Award DE-SC0019902)

The aim of this program was to gain a fundamental understanding of the behavior of various guest molecules in nano-confined environments, such as metal organic frameworks (MOFs), using a combination of novel synthesis, ab initio modeling, and in situ characterization. Through this project, we developed a concise understanding of the mechanisms that control adsorption/desorption of gaseous molecules and their mixtures, leading to design/synthesis guidelines for MOFs with desired functionality. We further developed methods to disentangle kinetic from thermodynamic effects during adsorption, as well as to characterize the interactions at play. In the first funding cycle, the focus was on the unambiguously characterization of co-adsorption and diffusion of gasses/vapors and their mixtures. In the second funding cycle, the focus was on characterizing the effects of the nano-confinement on the kinetics and thermodynamics of adsorption processes inside MOFs, again with an emphasis on mixtures of gasses and vapors. The nano-confinement can tip the thermodynamic vs. kinetic balance, and current understanding and theory based on single-component analysis can lead to incorrect predictions for mixtures. This is of particular interest in real-world applications, where gasses/vapors are typically mixed, contain impurities, or are often exposed to humid conditions. Our main findings were: (i) within confined environments the adsorption behavior of mixed gasses/vapors can be drastically different from the “sum” of the corresponding single phases; (ii) co-adsorption is often competitive and detrimental to performance, but it can also be cooperative and beneficial; (iii) in some co-adsorbed gasses/vapors, molecules that are strongly bound in the single-component phase can be replaced by molecules that are nominally weaker bound (molecular exchange) due to guest-guest interactions that lower the kinetic barriers and favor the final adsorption state; (iv) kinetic and thermodynamic effects can be precisely controlled through pore-size engineering and synthesis; and, (v) kinetic effects can be identified and disentangled from thermodynamic effects during adsorption through a series of sequential and simultaneous gas loading measurements. The short-term goal of this program was the controlling and understanding of common MOF systems in real-world situations where gasses/vapors are mixed, which will have an important impact on industrial processes and applications from gas storage and sequestration to catalysis and sensors. The long-term goals include the development of theoretical and experimental methods for gaining a fundamental understanding of adsorption/reaction processes within MOFs, as well as new guidelines for synthesizing MOFs with tailored physical and chemical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Adaptively controlled fast production of defect-free beryllium ion crystals using pulsed laser ablation

Trapped atomic ions find wide applications ranging from precision measurement to quantum information science and quantum computing. Beryllium ions are widely used due to the light mass and convenient atomic structure of beryllium; however, conventional ion loading from thermal ovens exerts undesirable gas loads for a prolonged duration. Here, we demonstrate a method to rapidly produce pure linear chains of beryllium ions with pulsed laser ablation, serving as a starting point for large-scale quantum information processing. Our method is fast compared to thermal ovens, reduces the gas load to only 10 -12 Torr (10 -10 Pa) level, yields a short recovery time of a few seconds, and also eliminates the need for a deep ultraviolet laser for photoionization. We also study the loading dynamics, which show non-Poissonian statistics in the presence of sympathetic cooling. In addition, we apply feedback control to obtain defect-free ion chains with desirable lengths.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Visualization and Analytics of Distribution Systems with Deep Penetration of Distributed Energy Resources (VADER)

In its current state, the distribution system is incapable of handling small to moderate amounts of photovoltaic (PV) penetration. This is because it was initially designed for handling passive loads which, at the level of a substation, have low variability and are forecastable with high accuracy. It has been an open loop system with little monitoring and control. With the addition of PV energy sources, the overall scenario will change dramatically due to (1) two way power flow on network; and (2) high aggregate variability. Additionally, changes on the consumption side lead to a number of smart loads, Electric Vehicles (EVs), and Demand Response. These fundamental changes in the characteristics of the generation and consumption of power will lead to a number of practical engineering problems which must be overcome to allow increased penetration of Distributed PV. Solving the unique engineering challenges which arise at moderate levels of PV penetration requires closed loop integration of data from (1) PV sources; (2) customer load data from smart meters; (3) EV charging data; and (4) local and line mounted precision instruments. These data are not traditionally used by utilities in operations since they are ”non-SCADA” and the current grid does not require such levels of control. To integrate this data and provide real time intelligence from these non-SCADA data, we created the Visualization and Analytics of Distribution Systems with Deep Penetration of Distributed Energy Resources (VADER) platform. VADER is a collection of analytics enabled by integration of massive and heterogeneous data streams for granular real-time monitoring, visualization and control of Distributed Energy Resources (DER) in distribution networks. VADER analytics enable utilities to have greater visibility into distributed energy resources. We built several batch- and stream-analytics in VADER which help operators better understand the impact of distributed energy resources on the grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Orthogonal Gelations to Synthesize Core–Shell Hydrogels Loaded with Nanoemulsion‐Templated Drug Nanoparticles for Versatile Oral Drug Delivery

Hydrophobic active pharmaceutical ingredients (APIs) are ubiquitous in the drug development pipeline, but their poor bioavailability often prevents their translation into drug products. Industrial processes to formulate hydrophobic APIs are expensive, difficult to optimize, and not flexible enough to incorporate customizable drug release profiles into drug products. Here, a novel, dual-responsive gelation process that exploits orthogonal thermo-responsive and ion-responsive gelations is introduced. This one-step “dual gelation” synthesizes core–shell (methylcellulose-alginate) hydrogel particles and encapsulates drug-laden nanoemulsions in the hydrogel matrices. In situ crystallization templates drug nanocrystals inside the polymeric core, while a kinetically stable amorphous solid dispersion is templated in the shell. Drug release is explored as a function of particle geometry, and programmable release is demonstrated for various therapeutic applications including delayed pulsatile release and sequential release of a model fixed-dose combination drug product of ibuprofen and fenofibrate. Independent control over drug loading between the shell and the core is demonstrated. This formulation approach is shown to be a flexible process to develop drug products with biocompatible materials, facile synthesis, and precise drug release performance. This work suggests and applies a novel method to leverage orthogonal gel chemistries to generate functional core–shell hydrogel particles.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Experimental Investigation of Gaseous Mixtures of Ethane, Methane, and Carbon Dioxide as an Alternative to Conventional Fuel in Spark Ignition Engines

This study investigates the viability and performance of certain synthetic fuels in spark ignition internal combustion engine based stationary power generation wherein the fuel comprises a mixture of methane and ethane in high dilutions of carbon dioxide (CO 2 ). The fuel of concern is a byproduct of a novel method for producing ethylene from ethane. The byproduct gas mixture has a concentration of approximately 41% CO 2 , 40% ethane, and 5% methane by weight along with other minor compounds. Varying mixtures of ethane and methane combined with between 42% and 46% by weight CO 2 were used to evaluate the viability and efficiency of this fuel to operate in existing internal combustion engines as a means of reducing emissions and increasing industrial process efficiency. A 13 hp gasoline generator was repurposed as a test stand by incorporating a modified fuel induction system and instrumentation for data collection. A gas metering and mixing system was installed to precisely control the mass flow of gases induced into the engine. Various instrumentations were installed to monitor in-cylinder pressure, temperature at various locations, emissions, and fuel and airflow rates. Varying fuel mixtures and loads were tested and compared to gasoline. It was found that under a high load, the mixed gas was able to generate comparable thermal efficiency and power to gasoline. But under no load or a part load condition the indicated thermal efficiency was found to be about 21% lower than that of gasoline. Further, the mixed gas also resulted in up to 50% reduction in CO and NOx emissions when compared to gasoline.

42 ENGINEERING↗
DOE OSTI2020

Airfoil leading edge blowing to control bow shock waves

Abstract This manuscript presents a detailed characterization of active control of bow shock waves via leading edge injection, including subsonic coolant ejection and the appearance of Coanda effects. The flow phenomena occurring at steady and pulsating flow injection regimes were analyzed using steady and unsteady two-dimensional Reynolds-Averaged Navier Stokes, leading to a precise evaluation of the thermal load and drag reductions. Steady supersonic injection yields the largest abatement in thermal load and aerodynamic drag, while subsonic or fluctuating ones can also provide significant improvements at reduced cooling mass flow rates. Furthermore, a Coanda effect, causing a non-symmetric flow topology, was observed and analyzed for reduced injection port size. This Coanda effect is due to the sudden expansion happening from the injection port to the main flow and it causes the flow topology at the leading edge to become non-symmetric despite the complete symmetry of the problem. This is the first time in the literature such a phenomenon is documented for a supersonic airfoil leading edge injection. Furthermore, it enables the design of novel flow control strategies for the leading edge shock topology and flow structures in supersonic flows.

42 ENGINEERING↗
DOE OSTI2025

A dual promotional effect of doping tantalum (Ta) in atomically dispersed Ru/CeO 2 catalyst toward CO 2 methanation: Enhanced associative adsorption of CO 2 and activation of H 2

Precisely controlling the product selectivity in CO 2 hydrogenation through rational catalyst design presents a promising approach to mitigate environmental and energy-related challenges, though it remains a significant scientific hurdle. Herein, the CH 4 selectivity of 0.5 wt% Ru loaded catalysts at 250 °C was effectively shifted from approximately 35 % to 100 % through the incorporation of Ta dopant into the CeO 2 support. The EXAFS spectra in conjunction with CO DRIFTS experiment indicated the presence of atomically dispersed Ru particles anchored on the Ta-doped CeO 2 surface. A higher oxidized CeO 2 surface was evidenced in the presence of Ta dopant. The presence of Ta dopant also improved the dispersion of Ru species and their interaction with the support. Most importantly, the Ru/Ta-CeO 2 catalyst exhibited a pronounced capacity for associative CO 2 -adsorption under atmospheric pressure at 50 °C. An improved H 2 activation was also observed under CO 2 hydrogenation conditions. This novel finding of the dual promotional effect of Ta carries a significant impact in the field of CO 2 capture and utilization.

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

Precise Motion Control of Hybrid Hydraulic Electric Architecture (HHEA)

Off-highway heavy-duty vehicles have been long-standing users of hydraulic systems for power transmission and control. However, traditional hydraulic systems suffer from significant energy losses which lead to increased operating costs and a larger carbon footprint due to higher CO2 emissions. Improving the efficiency of these mobile machines is crucial not only for reducing their environmental impact but also for saving billions of dollars in operating costs. Currently, the state-of-the-art Load Sensing Architecture uses throttling valves for control, which significantly reduces its efficiency and does not recuperate energy from over-running loads. Researchers have developed several architectures such as Common Pressure Rail systems, Displacement Control, STEAM, and Electrohydraulic Architecture to improve the efficiency of off-road mobile machines. However, each of these architectures has its drawbacks. To increase system efficiency and take advantage of electrification benefits, our research group has developed a novel Hybrid Hydraulic-Electric Architecture (HHEA). The HHEA can significantly improve efficiency, decrease the size of electrical components, and maintain control performance. This new architecture has the potential to revolutionize the off-highway mobile machine industry and lead to a more sustainable future. The HHEA uses a set of common pressure rails to provide the majority of power to the actuators via power-dense hydraulics and uses electric motors for precise control and power modulation. In the context of off-road mobile machines, energy savings are undoubtedly important but it is equally important to consider the machines’ ability to perform tasks with precision and accuracy according to given commands. Therefore, precise motion control is of utmost importance to maintain the utility of Hybrid Hydraulic-Electric Architecture (HHEA). The HHEA presents a unique challenge to motion control due to the discrete pressure changes that occur when the system switches between selected pressure rails. These changes are made to minimize system inefficiencies or to keep the system within the torque capability of the electric motor. Hence, it is important to solve the motion control challenges for HHEA. This thesis aims at developing an effective motion control strategy for HHEA. The dissertation presents a two-tiered control strategy for HHEA, comprising a high-level and a low-level controller. The primary responsibility of the high- level controller is to optimize energy efficiency by making informed pressure rail selections. On the other hand, the low-level controller is focused on achieving precise motion control of the HHEA, which is crucial for realizing the desired reference trajectories. To achieve this, the low-level controller utilizes a passivity-based backstepping integral controller as the nominal control, which handles the motion control between two pressure rail switches. Additionally, a separate least norm controller is utilized as a transition controller to manage motion control during pressure rail transitions. The effectiveness of the combined control strategy is demonstrated through experiments conducted on two hardware-in-the-loop testbeds. Furthermore, the HHEA is installed on the boom and stick actuators of a backhoe arm to build a Human-in-the-Loop system that a human operator can control. A real-time rail switching algorithm is developed to determine pressure rail switching based on present duty cycle information from the operator. Modifications have been made to the human-machine interface to achieve more intuitive control. Modifications include performing control in the task-oriented coordinates, incorporating pressure feedback to enhance control with physical interaction, and using velocity field control to simplify multi-degree-of-freedom tasks and to enable novice operators to perform them with reduced risk, improved efficiency, and productivity. The research in this dissertation makes significant contributions to the field of off-road mobile machine control, providing a novel and effective control strategy for the HHEA, and demonstrating the potential for simplified machine operation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

General Testing Setup for Hyperelastic Transducers-DEEC-Tec & Marine Renewable Energy: Preprint

Distributed embedded energy conversion technologies (DEEC-Tec), an emerging domain for ocean wave energy conversion technology, is showing promise for a range of applications. Research is being conducted at the National Renewable Energy Laboratory that leverages this domain to investigate the potential of ocean wave energy converters (WECs) constructed from hyperelastic forms of distributable and embeddable energy transducers. These transducers are available in forms such as disks, rectangles, or hexagons and can be combined in various ways to form energy-producing metamaterials and flexible WECs. DEEC-Tec, therefore, could open doors that enhance ocean wave energy conversion in ways not previously thought possible by allowing for many WEC topologies and morphologies. However, the same diversity and adaptability pose challenges for the development of these DEEC-Tec-oriented hyperelastic transducers. A commercial tensile testing setup was not found that was adaptable enough to accommodate the varied transducers while providing precise force control, range of motion, and noncontact data collection. Because of this lack, a comprehensive test rig was designed in house to be used with a 3D laser scanning device-providing contactless measurements while also allowing for different geometries and various uniaxial loadings. This paper and presentation will discuss these unique challenges and the processes for overcoming them to provide a robust and general testing setup for hyperelastic transducers, of any form, for the DEEC-Tec marine renewable energy domain.

DEEC-Tec↗