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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 289 records · Page 16

NMPC for Mode-Switching Operation of Reversible Solid Oxide Cell Systems

Solid oxide cells (SOCs) are a promising dual-mode technology that generates hydrogen through high-temperature water electrolysis and generates power through a fuel cell reaction that consumes hydrogen. Reversible operation of SOCs requires a transition between these two modes for hydrogen production setpoints as the demand and price of electricity fluctuate. Moreover, a well-functioning control system is important to avoid cell degradation during mode-switching operation. In this work, we apply nonlinear model predictive control (NMPC) to an SOC module and supporting equipment and compare NMPC performance to classical proportional integral (PI) control strategies, while ramping between the modes of hydrogen and power production. While both control methods provide similar performance in many metrics, NMPC significantly reduces cell thermal gradients and curvatures (mixed spatial-temporal partial derivatives) during mode switching. A dynamic process flowsheet of the reversible SOC system was developed in the open-source, equation-based IDAES modeling framework. Our IDAES dynamic simulation results show that NMPC can ramp the SOC system between hydrogen and power production targets within short mode-switching times. Moreover, NMPC can comply with operating limits in the SOC system more effectively than PI, and only NMPC can directly enforce user-specified limits for mixed spatial-temporal partial derivatives of temperature. This allows for management of the trade-off be-tween operating efficiency and cell degradation, which is dependent on these temperature curvatures.

Li, Mingrui↗

NMPC for Setpoint Tracking Operation of a Solid Oxide Electrolysis Cell System

Solid oxide electrolysis cells (SOECs) are a promising technology to generate hydrogen through water electrolysis. However, intermittent renewable energy requires SOECs to transition between hydrogen production setpoints as the price of electricity fluctuates. A well-functioning control system is important to avoid cell degradation during setpoint tracking operation. In this work, we apply nonlinear model predictive control (NMPC) to an SOEC module and supporting equipment and compare NMPC performance to classical PI control while ramping between hydrogen production setpoints. We find that these control methods provide similar performance in many metrics, but NMPC significantly reduces cell thermal gradients during the setpoint transition.

Allan, Douglas↗

AN EXPERIMENTAL STUDY OF FUEL SELECTION FOR A GASOLINE MULTI-MODE

In this study of fuels of different reactivities and their performance in a low-temperature combustion (LTC) engine. The engine was a 2.2L CRDI engine code D4HB provided by industry partner Hyundai America Technical Center inc. (HATCI). The engine was instrumented with in-cylinder pressure sensors allowing for monitoring of the combustion process. First, the engine was operated with standard US pump grade gasoline, Research Octane number (RON) 91 E10, to find initial operation conditions as well as control points of stable operation for daily checks on system conditions. Tested were 8 different fuel blends, the four base blends were provided by Phillips 66 (P66) with a RON value ranging from 60 to 91, and three other variations of these fuels were formulated by splash blending alcohols, iso-butanol, and ethanol, with the RON60 fuel and the final blend, was US RON91 E10 pump gasoline. Using these 8 fuels, the low load performance was analyzed allowing a selection of one of the fuels to be made to proceed with experimentation. To study the low load performance of each fuel, the load was decreased until combustion became too unstable to continue. This was done at 1500 rpm with all of the fuels. At 1200 rpm, the same methodology was applied, though all of the fuels were not tested, only the fuels which showed promise at 1500 rpm. Meaning that the lowest targeted load was achieved without any aid to the combustion process other than advancing combustion, increasing intake air temperature (IAT) for example was not done to maintain consistency across all fuels. The same methodology was applied at 800 rpm based upon the 1200 rpm results to see the ability of the engine to idle with the given fuel. It was found that fuel with a RON of 80 showed good low load performance while allowing for high load performance to be maintained. A blend of 25% Iso-Butanol and 75% RON 60 equated to a RON of 80 and showed good low load performance and showed peak indicated thermal efficiency (ITE) numbers of 46% at 17 bar indicated mean effective pressure (IMEP) and 2200 rpm.

02 PETROLEUM↗

A Mixed Integer Linear Programming-basedDistributed Energy Management for Three-phaseUnbalanced Active Distribution Network

A mixed integer linear programming (MILP)–baseddistributed energy management for three-phase unbalancedactive distribution network is proposed. Modern distributionnetworks have becoming more and more active with increasingdeployment of microgrids, distributed energy resources (DERs)as well as controllable loads. Considering various ownership andcontrol models of microgrids, DERs and controllable loads, adistributed energy management was formulated using the alternatingdirection method of multipliers (ADMM) algorithm. ByADMM, the distribution management system (DMS) and theseactive components are coordinated through price signals, whichare adjusted according to the generation-load mismatch per nodeper phase. To enable resolution of the ADMM-based distributedoptimization using more accessible and popular MILP solver,different linearization techniques were proposed to linearize theaugmented Lagrangian terms and other nonlinear terms. Resultsof case studies on a three-phase active distribution network withthree microgrids and several DERs and controllable loads validatedthe effectiveness of proposed MILP-based distributed energymanagement. In addition, the capability of proposed method inmitigating phase power unbalance has been demonstrated.

Liu, Guodong↗

AN AUTOMATED ANCHORING SYSTEM FOR AN UNMANNED SURFACE VEHICLE

The goal of this thesis is to simulate, design and build an automated device that allows unmanned vessels to anchor themselves in specified locations while being United States Coast Guard Navigation Rules compliant. This is a part of a larger project funded by the U.S. Department of Energy for Florida Atlantic University to build an unmanned platform with an Undershot Water Wheel on it. By simulating the environment of the South Florida Intercoastal Water Ways, forces acting on the line, anchor and the vessel are analyzed. These forces are used as the guide for the design and build of a line locking mechanism that takes the tension off the winch and a sensor package to monitor the environment the platform is in as well as control of the system. Based off experimental testing, the system was successful in handling all emulated environments with loads exceeding 150lbs of tension.

Fosbrook, Amanda↗

Cryogenic RF characterization of the MAGO cavity for high-frequency gravitational-wave detection

Superconducting radio-frequency (SRF) cavities are promising resonant sensors for gravitational-wave detection in the kHz-MHz frequency range. We report the cryogenic RF characterization of a prototype superconducting niobium cavity with an unconventional geometry designed for narrow electromagnetic mode separation. Following an adapted surface preparation procedure, cryogenic tests were performed at Fermilab and DESY at temperatures down to 2 K. Mechanical tuning at room temperature achieved a mode splitting of approximately 11 kHz at cryogenic temperature. High electromagnetic quality factors consistent with previous prototype cavities were measured. The measurements further revealed phase transfer characteristics relevant for stable low-level RF control as well as indications of mode coupling potentially caused by one-point multipacting. In addition, first cryogenic measurements of the mechanical eigenmodes yielded mechanical quality factors significantly below commonly assumed theoretical values. These results demonstrate the successful application of established SRF preparation and characterization techniques to a non-standard resonator geometry and provide important experimental input for the development of future SRF-based gravitational-wave detectors.

Dokuyucu, Can [DESY]↗

A High-Efficient Solution for Electro-Hydraulic Actuators with Energy Regeneration Capability

This paper proposes a cost-effective, robustly practical solution for a high-efficient electro-hydraulic actuator (EHA) for linear drives. The solution addresses the challenges of high costs and limited efficiency that limit the application of EHA for the electrification of many off-road vehicles. Based on a variable-speed electric motor and a low-cost technology for a fixed-displacement pump, the proposed solution is suitable for a compact implementation and it is capable of energy regeneration under overrunning load conditions. Two different architectures—an open circuit and a closed circuit one—are considered to determine the most practical and efficient configuration as well as the control features. Both architectures minimize throttling losses associated with the conventional regulation of hydraulic actuators. Actuator velocities below the minimum and beyond the maximum allowable pump flow rate are achieved in both architectures using a proportional valve that bypasses the pump flow. The paper describes the design methodology as well as the simulation and experimental activities performed to verify the control strategies as well as energy efficiency. Considering an EHA system of about 20 kW, a complete efficiency map of the system is determined for all the possible four quadrants of operation thus including both resistive and overrunning loads, where energy recuperation is implemented. Simulation and experimental results show that the energy efficiency of the hydraulic systems can reach 84.7% in resistive phases. In assistive phases, the hydraulic system can recover up to 81.8% of the actuator energy. Here, the comparison between open-circuit and closed-circuit structures shows the advantages of the former in terms of energy efficiency. The proposed solution is suitable for electrified hydraulic actuation systems, in both industrial and mobile applications. With the advantages of the low cost of the hydraulic unit and high energy efficiency, it is particularly suitable for mobile applications such as construction machines, that are recently experiencing a significant electrification trend.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Use of a Lignin-Based Admixture for Tailoring the Rheological Properties of Mortars for 3D Printing: Preprint

Efforts toward decarbonizing construction materials and industrial processes related to cement and concrete can be aided via multifaceted approaches that target alternative admixtures as well as precision control of fabrication. Chemical admixtures for water reduction have played a crucial role in the development of advanced concrete mixtures. Newer biomass processing techniques developed for aviation fuel production from corn stover biomass produce a more reactive lignin byproduct that is suitable for chemical modifications to mimic the properties of polycarboxylate ether admixtures with a smaller carbon footprint. The present study examines the use of lignin-based water-reducing admixture in cement pastes and mortar mixtures for 3D printing. The experimental program explores the use of different dosages of lignin-based admixture to produce 3D-printed samples with appropriate extrudability and buildability. The rheological characterization was performed to determine the flow curve of various mixtures. Finally, the heat of hydration of cement pastes was monitored via isothermal calorimetry to assess the impact of lignin-based admixtures on the hydration process of cement. The results of this study indicate that the use of biomass by-products, such as lignin-based admixtures have great potential to effectively control the fresh-state properties of cement-based materials.

bio-based admixtures↗

Hardware-in-the-loop Laboratory Performance Verification of Flexible Building Equipment in a Typical Commercial Building

This project aims to develop high-resolution equipment performance and occupant data that quantifies demand flexibility in typical commercial buildings. The dataset documented in this report includes comprehensive time-series measurements from hardware-in-the-loop (HIL) experiments conducted across multiple testbeds designed to simulate realistic operational environments for HVAC systems. Specifically, it captures minute-by-minute high-resolution data on the performance of various typical HVAC systems, including a variable-air-volume (VAV) air handling unit (AHU) system with chillers and an ice tank in the Intelligent Building Agents Laboratory (IBAL) at the National Institute of Standards and Technology (NIST), a two-stage air-source heat pump (ASHP) at the NIST, and a water-source heat pump (WSHP) at Texas A&M University (TAMU). The data were generated under a range of controlled conditions reflecting different grid scenarios and climatic influences, as well as various control strategies, building types, occupancy patterns, and occupant behaviors. This dataset provides DE-EE0009153 Final Report 5 detailed insights into the demand flexibility of these systems, including their response to grid signals, occupant behaviors, energy consumption patterns, and operational efficiency under different conditions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Current state and future trends in boundary layer control on lifting surfaces

Successful flow control may bring numerous benefits, such as flow stabilization, flow reattachment, separation delay, drag reduction, lift increase, aerodynamic performance improvement, energy efficiency increase, shock delay or weakening, noise reduction, etc. For these purposes, many different flow control devices, which can be classified as passive, semi-active and active, have been designed and tested. This review paper aims to highlight the most promising and commonly employed boundary layer control methods as well as outline their potential in specific applications in aerospace and energy engineering. Referenced studies, performed on various geometries (flat plates, channels, airfoils, wings, blades, cylinders), are primarily numerical or experimental. Although enhanced aerodynamic performance is achieved in many cases, further research is required to draw general conclusions. This paper aims to demonstrate that, in the future, we may expect further developments of flow control actuators, as well as their increased application.

42 ENGINEERING↗

Feed-Forward Compensation for Model Predictive Control in Tri-port Current-Source Medium-Voltage String Inverters for PV-Plus-Storage Farms

The novel tri-port current-source medium-voltage string inverter (TCS-MVSI) is a promising candidate for large-scale PV-plus-storage (PVS) farms owing to its galvanic isolation, easy storage integration, soft-switching capability across entire load range, controlled low dv/dt and EMI, benign fault tolerance, etc. Due to its low inertia feature, traditional PI-based control cannot manage large transients effectively. Instead, a model-based predictive control (MPC) is proposed to achieve robust and stable operation. As is well known, the control performance of MPC is compromised by the sampling and computational delay during implementation significantly, if not well addressed. This paper analyzed and quantified these delays and then proposes feed-forward compensation (FFC) for the MPC method to compensate the delays and the large parameter variations due to the low-inertia nature. In addition, this method also compensates for the high dc-link ripple within each switching cycle, a unique issue for low-inertia converters. Here, the proposed method requires low computational effort, allowing it to be extended for multiple ports. The effectiveness of the proposed method has been validated in experiments. In 10 kW test, the proposed method decreases the average dc-link current by 17%, leading to ~20% conduction losses and ~0.5% increase in converter efficiency. In addition, the peak dc-link current also decreases by 15%, resulting in reduced transformer size. As a result, an increased power density can be achieved with the proposed method. Similar improvements have been observed across the power range from 2 kW to 10 kW.

30 DIRECT ENERGY CONVERSION↗

Multi-Agent Control of Lane-Switching Automated Vehicles for Energy Efficiency

The proliferation of automatic control systems and their connectivity accents the performance of their interactions. In particular, connected and automated vehicles could become high-impact examples thanks to their energy use and productivity effects. Ideally, a controller might collectively optimize all agents' control moves for a given objective. However, limits on computational complexity, incomplete knowledge of the central planner, and risks of a single point of failure make distributed control attractive as well. This paper proposes a collaborative heuristic to approach the performance of centralized control with decentralized-like computational effort. The related centralized controller is also described in detail and evaluated as a baseline. A collaboration-intensive obstacle avoidance scenario involving electric vehicles is simulated to demonstrate benefits over fully decentralized control. While centralized optimization performed best with an 8.6 % energy reduction, the collaborative decentralized scheme reached a favorable computation-performance tradeoff with a 6.7 % energy reduction.

Dollar, R. Austin↗

2023 Real-time Optimization Workflow Status Update

Nuclear integrated energy systems are composed of a diverse set of energy generation sources and exist in dynamic and competitive electricity markets. With the inclusion of thermal energy storage, nuclear power systems can store heat for future use through various processes, such as water desalination or hydrogen generation. This heat storage can be managed in such a way as to economically optimize its usage. By combining real-time price data from the day-ahead and real-time markets with predictive and intelligent models, the charging and discharging of the thermal energy storage may be determined and optimized. This research details an approach through models and systems for the real-time optimization (RTO) of capacity allocation. Virtual models of the energy system and its physics phenomenon and component interactions provide intelligence to verification and prediction of operations. An optimization framework can use data generated from both a set of physical assets as well as the virtual models to predict future performance and create optimization and control workflows. Data warehouse technologies can be used to combine data across models, optimization workflows, market price data, and sensor data to intuitively store various types of data and provide integrations to physical control systems as well as user visualizations. Put together, these components can create a system for the RTO of nuclear integrated energy systems. Various virtual models and bench-scale physical demonstrations have been successfully performed and verified using this system. Larger scale testbeds that include thermal energy storage systems have been identified as future opportunities. A gap analysis that details the steps necessary to reach a physical demonstration at this scale is provided, along with conclusions on the current effort and future work.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Commercial Building Sensors and Controls Systems: Barriers and Drivers: Preprint

Building sensors and controls systems, including building automation systems, comprise the sensor-based devices installed in buildings as well as the control and automation of those devices. Optimized sensors and controls systems could lead to 29% annual energy savings in commercial buildings and are integral to the growth of grid-interactive efficient buildings. Only 13% of small commercial buildings, however, have installed sensors and controls systems, largely because of cost barriers. To accelerate adoption, this work seeks to increase the transparency of system costs and identify specific barriers and drivers. To gather industry insights, the team reached out to building owners, vendors, and contractors and conducted 21 interviews with the goal of collecting cost data and market characteristics regarding building sensors and controls. We collected the cost data in the form of invoices and used it to develop a percentage-based cost category breakdown. The interview data were analyzed using grounded theory to identify overarching concepts such as barriers, drivers, and future directions. From this analysis, we found the primary barriers to be complex and confusing systems, lack of user skills, and financial concerns, and the primary drivers to be operational benefits, insight into operations, and remote access to data. The future directions analysis highlighted the potential technological solutions to address gaps and barriers, as well as predicted drivers to increase adoption. This greater understanding of the costs, barriers, and drivers associated with commercial building sensors and controls systems lays the groundwork for increasing system adoption, reducing energy consumption, and transforming the market.

building automation system↗

A Predictive Deep-Reinforcement-Learning-Based Connected Automated Vehicle Anticipatory Longitudinal Control in a Mixed Traffic Lane Change Condition

Maintaining safety and efficiency for mixed traffic consisting of connected automated vehicles (CAVs) and human-driven vehicles (HDVs) is an arduous task due to the inherent HDVs’ stochasticity. Especially for longitudinal control, which is the basic function of vehicle automation, prevailing research primarily considers CAV’s car-following control merely the acceleration and deceleration of leading vehicles. However, this approach overlooks the potential disruptions caused by surrounding vehicles executing lane changes, which can significantly impact the control vehicle’s stability and overall safety. Hence, our study introduces a predictive deep reinforcement learning (DRL) longitudinal CAV controller. This innovative approach leverages prediction from a physics-informed neural network as well as the control capability of DRL to better anticipate and mitigate issues arising from lane-changing, enhancing the safety and efficiency of CAVs in such scenarios. Finally, validated by the numerical simulations embedded with the real-world data, the results indicate that the proposed controller significantly enhances the safety and efficiency of CAVs in situations involving lane changes by other vehicles, showcasing its potential as a valuable tool in advancing CAV technology in mixed traffic.

33 ADVANCED PROPULSION SYSTEMS↗

High-Throughput Microfluidic Electroporation (HTME): A Scalable, 384-Well Platform for Multiplexed Cell Engineering

Electroporation-mediated gene delivery is a cornerstone of synthetic biology, offering several advantages over other methods: higher efficiencies, broader applicability, and simpler sample preparation. Yet, electroporation protocols are often challenging to integrate into highly multiplexed workflows, owing to limitations in their scalability and tunability. These challenges ultimately increase the time and cost per transformation. As a result, rapidly screening genetic libraries, exploring combinatorial designs, or optimizing electroporation parameters requires extensive iterations, consuming large quantities of expensive custom-made DNA and cell lines or primary cells. To address these limitations, we have developed a High-Throughput Microfluidic Electroporation (HTME) platform that includes a 384-well electroporation plate (E-Plate) and control electronics capable of rapidly electroporating all wells in under a minute with individual control of each well. Fabricated using scalable and cost-effective printed-circuit-board (PCB) technology, the E-Plate significantly reduces consumable costs and reagent consumption by operating on nano to microliter volumes. Furthermore, individually addressable wells facilitate rapid exploration of large sets of experimental conditions to optimize electroporation for different cell types and plasmid concentrations/types. Use of the standard 384-well footprint makes the platform easily integrable into automated workflows, thereby enabling end-to-end automation. We demonstrate transformation of E. coli with pUC19 to validate the HTME's core functionality, achieving at least a single colony forming unit in more than 99% of wells and confirming the platform's ability to rapidly perform hundreds of electroporations with customizable conditions. This work highlights the HTME's potential to significantly accelerate synthetic biology Design-Build-Test-Learn (DBTL) cycles by mitigating the transformation/transfection bottleneck.

Gaillard, William R↗

Integrated solid-state rapid thermo-cycling system

Techniques, systems, and devices are disclosed for implementing a portable lab system for PCR testing. The portable lab system comprises a thermal cycling device including a first well and a second well to receive samples to be thermally cycled, a thermoelectric cooling (TEC) element coupled to the first well and the second well, and a controller to control operation of the TEC element. The portable lab system further includes an electronic interface including a power interface to supply power to the TEC element and the controller of the thermal cycling device to allow the TEC element to transfer energy from the first well to the second well when current flows through the TEC element in a first direction, and from the second well to the first well when current flows through the TEC element in a second direction, and a data interface to collect data from the controller.

59 BASIC BIOLOGICAL SCIENCES↗

DSP Implementation of a Novel Recurrent Neural Network Controller into a TI Solar Microinverter

Single-phase grid-tied inverters are widely used to integrate small-scale renewable energy sources and distributed generations to the utility grid. A novel Recurrent Neural Network (RNN) current controller is introduced to solve the resonant problem associated with LCL based inverters. The well-trained RNN controller was validated through a Texas Instruments (TI) LCL filter based solar microinverter kit that contains a C2000 TI microcontroller. The inverter closed current loop test without the grid connection was conducted in a laboratory setup to verify the RNN contoller functionality. The laboratory waveform results verified that the RNN current controller produced the strong tracking of the measured inverter AC current to its reference value even at a low sampling frequency of 5KHz. The proposed RNN current controller also proved to perform better than the built-in three-pole-three-zero (3P3Z) current controller provided by TI and produce lower values of Total Harmonic Distortion (THD).

digital signal processor↗