LCOE Content Model for the Heaving Point Absorber Buoy
This is the LCOE analysis spreadsheet and content model for the heaving point absorber buoy developed for controls purposes. The cost assessment was done on a wave-farm of 100-units.
1-DoF↗
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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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Wave Tank Testing Report for Controls Validation of a Heaving Point Absorber
The core objectives of this project is to improve the power capture of three different wave energy conversion (WEC) devices by more than 50% using an advanced control system and validate the attained improvements using wave tank and full scale testing. In parallel, we will bring along the development of a wave prediction system that is required to enable effective control and test it at full scale. The purposes of this report are to: 1. Plan and document the 1/25th scale device testing at the wave-tank facility; 2. Document the test article, setup and methodology, sensor and instrumentation, mooring, electronics, wiring, and data flow and quality assurance; 3. Communicate the testing results between the associated members; 4. Facilitate reviews that will help to ensure all aspects (risk, safety, testing procedures, etc.); 5. Provide a systematic guide to setting up, executing and decommissioning the experiment.
16 TIDAL AND WAVE POWER↗
Effects of Mineral Surface Properties on Supercritical CO 2 Wettability in a Siliciclastic Reservoir
Wettability is a key reservoir characteristic influencing geological carbon sequestration (GCS) processes, such as CO 2 transport and storage capacity. Wettability is often determined on a limited number of reservoir samples by measuring the contact angle at the CO 2 /brine/mineral interface, but the ability to predict this value remains a challenge. In this work, minerals comprising a natural reservoir sample were identified, and the influence of their surface roughness and mineralogy on the contact angle was quantified to evaluate predictive models and controlling mechanisms. The natural sample was obtained from the Mount Simon formation, a representative siliciclastic reservoir that is the site of a United States Department of Energy CO 2 injection project. A thin section of the Mount Simon sandstone was examined with compound light microscopy and environmental scanning electron microscopy (ESEM) coupled with energy-dispersive X-ray spectroscopy (EDS). Quartz and feldspar were identified as dominant minerals and were coated with various reddish black precipitates consistent with illite clay and iron oxide hematite. Contact angle (θ) measurements were conducted for the four representative minerals and the Mount Simon sample over a range of pressures (2–25 MPa) at 40 °C. At supercritical conditions, all samples are strongly water-wet, with contact angles between 27° and 45°. Several predictive models for contact angle were evaluated for the mineral and Mount Simon samples, including the Wenzel and Cassie–Baxter models, plus newly proposed modifications of these that account for the fraction of different minerals comprising the reservoir sample surface, the surface roughness, and the extent that roughness pits are filled with brine. Modeling results suggest that the fraction of mineral surfaces containing roughness pits filled with brine is the most important reservoir characteristic that controls wettability in the Mount Simon sandstone, followed by surface mineralogy. Finally, to our knowledge, this is one of the few studies to investigate the effects of individual minerals on the wettability of a natural reservoir sample.
58 GEOSCIENCES↗
Investigation of Reduced-Order Modeling for Aircraft Stability and Control Prediction
High-fidelity computational fluid dynamics tools offer the potential to approximate increments for ground-to-flight scaling effects, as well as to augment the dynamic damping derivative data for motion-based flight simulators. Unfortunately, the computational expense is currently prohibitive for populating a complete simulator database. This work investigates an existing surrogate-based, indicial response reduced-order model methodology as a means to efficiently augment a flight simulator database with high-fidelity nonlinear aerodynamic damping derivatives. Creation of the reduced-order model is based on the superposition integrals of the step response with the derivative of its corresponding input signal. Step responses are calculated using a computational grid motion approach that separates the effects of angle of attack and sideslip angle from angular rates, and rates from angle of attack and sideslip. It is demonstrated that the transients produced during the start of a forced-oscillation motion are captured by the reduced-order model to the level of fidelity of a comparable computational solution. Aerodynamic coefficients computed within minutes by the reduced-order model for an aircraft undergoing an 18-second half Lazy-8 maneuver and a 25-second Immelmann turn maneuver are compared with those from full computational flight solutions that required days to complete. Finally, a cost-benefit assessment is included that demonstrates a compelling advantage for this approach. d for maneuvering, flexible vehicles.
Frink, Neal T.↗
IoT-Based Comfort Control and Fault Diagnostics System for Energy-Efficient Homes
This project studies an Internet of Things (IoT)-based comfort control and fault diagnostics system (referred as iComfort in this report) for energy-efficient homes. The system delivers an occupant-comfort-oriented thermal environment adaptive to fault scenarios and achieves HVAC energy savings in a cost-effective and straightforward way. This smart iComfort home system consists of the following key features. 1) Cost-effectiveness and scalability of the entire hardware and software system: The system includes low-cost temperature, humidity, and airflow sensors, and a Raspberry Pi-based local hub that interfaces with the cloud and IoT-enabled devices. The cost is low, not only for sensors, but also the costs associated with sensor installation, system setup and commissioning, data communication and storage, and data analytics (e.g., the development of automated fault detection and diagnosis (AFDD), as well as adaptive control strategies that are both computationally efficient and practical to implement). 2) Energy performance and user satisfaction: The system delivers user satisfaction and energy savings. This includes a) ease of use, b) optimal occupant thermal comfort, and c) accurate system feedback (e.g., low false alarm of AFDD strategies). 3) Favorable demonstrated prototype performance: The prototype tested at the Pacific Northwest National Laboratory (PNNL) Lab Homes demonstrates the accuracy of fault detections and diagnoses and shows thermal comfort improvement and energy savings through adaptive and optimal HVAC operations.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Scalable, Data-Driven, and High-Resolution Building Models for Control Optimization
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32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Automated model-predictive design of synthetic promoters to control transcriptional profiles in bacteria
Abstract Transcription rates are regulated by the interactions between RNA polymerase, sigma factor, and promoter DNA sequences in bacteria. However, it remains unclear how non-canonical sequence motifs collectively control transcription rates. Here, we combine massively parallel assays, biophysics, and machine learning to develop a 346-parameter model that predicts site-specific transcription initiation rates for any σ 70 promoter sequence, validated across 22132 bacterial promoters with diverse sequences. We apply the model to predict genetic context effects, design σ 70 promoters with desired transcription rates, and identify undesired promoters inside engineered genetic systems. The model provides a biophysical basis for understanding gene regulation in natural genetic systems and precise transcriptional control for engineering synthetic genetic systems.
42 ENGINEERING↗
A Modeling Approach for Handling Qualities and Controls Safety Analysis of Electric Air Taxi Vehicles
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Urban Air Mobility,Air Taxi,Flight Dynamics,Model ↗
Advanced control strategies to manage electric vehicle drivetrain battery health for Vehicle-to-X applications
Not Available
33 ADVANCED PROPULSION SYSTEMS↗
Novel PCM Integration with Electrical Heat Pump for Demand Response
In this paper, we examine the potential for using phase change material (PCM) as a thermal storage medium for improving the efficiency as well as enabling grid-responsive control of heat pump (HP) systems. Previous research in PCM integration in buildings has primarily been focused on integration with building envelopes. An objective of our research is to design a novel and practical PCM integration with existing HP systems. High-fidelity models for building, HP and PCM are developed to facilitate the model-based predictive control (MPC) design. To optimize the operation of HP and PCM, we introduce an optimization problem considering various constraints for both comfort and hardware constraints. We include experimental results in which a house fleet are optimized to minimize their power consumption or electricity cost. We numerically demonstrate the designs potential for reducing power consumption or electricity cost by 13% or 19%, respectively.
Dong, Jin↗
Numerical and Experimental Investigation of Turbulent Transport Control via Shaping of Radial Plasma Flow Profiles (Final Technical Report)
The strong coupling between the different physical variables involved in the plasma transport phenomenon and the high complexity of its dynamics call for a model-based, multivariable approach to profile control where those predictive models could be exploited. The overall objective of this project has been to extend the existing body of work by investigating numerically and experimentally active control of unstable fluctuations, including fully developed turbulence and the associated cross-field particle transport, via manipulation of flow profiles in a magnetized laboratory plasma device. Fluctuations and particle transport can be monitored by an array of electrostatic probes, and E x B flow profiles can be controlled via a set of biased concentric ring electrodes that terminate the plasma column. The goals of the proposed research have been threefold: i- to develop a predictive code to simulate plasma transport in the linear HELCAT (HELicon-CAThode) plasma device at the University of New Mexico (UNM), where the experimental component of the proposed research has been carried out; ii- to establish the feasibility of using advanced model-based control algorithms to control cross-field turbulence-driven particle transport through appropriate manipulation of radial plasma flow profiles, iii- to investigate the fundamental nonlinear dynamics of turbulence and transport physics. Lehigh University (LU), including Prof. Eugenio Schuster and one full-time graduate student, has been primarily responsible for control-oriented modeling and model-based control design. Undergraduate students have also participated in this project through the National Science Foundation Research Experience for Undergraduate (REU) program. The main goal of the LU Plasma Control Group has been to study the feasibility of controlling turbulence-driven transport by shaping the radial poloidal flow profile (i.e., by controlling flow shear) via biased concentric ring electrodes.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Synchrophasor-Based Auxiliary Controller to Enhance the Voltage Stability of a Distribution System With High Renewable Energy Penetration
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24 POWER TRANSMISSION AND DISTRIBUTION↗
Understanding structure-processing relationships in metal additive manufacturing via featurization of microstructural images
Understanding and predicting accurate property-structure-processing relationships for additively manufactured components is important for both forward and inverse design of robust, reliable parts and assemblies. While direct mapping of process parameters to properties is sometimes plausible, it is often rendered difficult due to poor microstructural control. Exploring the direct relationship between processing conditions and microstructural features can thus provide significant physical insights and aid the overall design process. Here, in this study, we develop an automated high-throughput framework to simulate an uncertainty-aware additive manufacturing (AM) process, characterize microstructural images, and extract meaningful features/descriptors. A kinetic Monte Carlo (KMC) based model of the AM process is used to simulate microstructural evolution for a diverse set of experimentally relevant processing conditions. We perform a parametric study to explore the relationship between microstructural features and processing conditions. Our results indicate that a many-to-one mapping can exist between processing conditions and typical descriptors; therefore, multiple descriptors are thus necessary to unambiguously represent microstructural images. Our work provides crucial quantitative and qualitative in-formation that would aid in the selection of features for microstructural images. Featurized microstructures could then be utilized to build data-driven models for predictive control of microstructures and thereby properties of additively manufactured components.
36 MATERIALS SCIENCE↗
The Heuristic Dynamic Programming Approach in Boost Converters
In this study, a heuristic dynamic programming controller is proposed to control a boost converter. Conventional controllers such as proportional-integral-derivative (PID) or proportional-integral (PI) are designed based on the linearized small-signal model near the operating point. Therefore, the performance of the controller during the start-up, the load change, or the input voltage variation is not optimal since the system model changes by varying the operating point. The heuristic dynamic programming controller optimally controls the boost converter by following the approximate dynamic programming. The advantage of the HDP is that the neural network-based characteristic of the proposed controller enables boost converters to easily cope with large disturbances. An HDP with a well-trained critic and action networks can perform as an optimal controller for the boost converter. To compare the effectiveness of the traditional PI-based and the HDP boost converter, the simulation results are provided.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Predictive Workload Model for Air Traffic Controllers during UAM Operations
The effect of airspace factors on air traffic controller (ATC) workload has been an active area of study for almost three decades due to the importance of safety considerations necessary to design and maintain operations. Existing literature has examined several traffic-related (e.g., number of aircraft under control, loss of separation) contributors to ATC workload and proposed mathematical functions to best describe controller response. However, future air traffic continues to increase in complexity with the introduction of urban air mobility (UAM) – or the transportation of humans and cargo using electric vertical takeoff and landing (eVTOL) aircraft. UAM aims to alleviate congestion for existing ground transportation systems and improve mobility within urban centers and other high-demand locations. This shift in the traditional airspace paradigm necessitates an evolved understanding of model use and development for ATC workload prediction. This study aimed to develop an ATC workload forecasting model based on human-in-the-loop (HITL) simulation data for UAM operations at large airports. Data collected from the HITL simulation served as the training and testing data for a Long Short-Term Memory recurrent neural network and enabled time-series forecasting of ATC workload from traffic characteristics. Results demonstrated the potential of LSTM models for forecasting ATC workload 40 minutes into the future and highlighted important considerations for future development.
predictive model↗
Predictive Workload Model for Air Traffic Controllers during UAM Operations
The effect of airspace factors on air traffic controller (ATC) workload has been an active area of study for almost three decades due to the importance of safety considerations necessary to design and maintain operations. Existing literature has examined several traffic-related (e.g., number of aircraft under control, loss of separation) contributors to ATC workload and proposed mathematical functions to best describe controller response. However, future air traffic continues to increase in complexity with the introduction of urban air mobility (UAM) – or the transportation of humans and cargo using electric vertical takeoff and landing (eVTOL) aircraft. UAM aims to alleviate congestion for existing ground transportation systems and improve mobility within urban centers and other high-demand locations. This shift in the traditional airspace paradigm necessitates an evolved understanding of model use and development for ATC workload prediction. This study aimed to develop an ATC workload forecasting model based on human-in-the-loop (HITL) simulation data for UAM operations at large airports. Data collected from the HITL simulation served as the training and testing data for a Long Short-Term Memory recurrent neural network and enabled time-series forecasting of ATC workload from traffic characteristics. Results demonstrated the potential of LSTM models for forecasting ATC workload 40 minutes into the future and highlighted important considerations for future development.
predictive model↗
Predictive Direct DC-Link Control for 7.2 kV Three-Port Low-Inertia Solid-State Transformer With Active Power Decoupling
Promising for applications including renewable energy and electric vehicle fast charging, a medium-voltage (MV) solid-state transformer (SST) typically has multiple modules series stacked, which requires the modules to be single phase. One critical issue of the single-phase SST is the double-line-frequency power ripple. Traditionally, large passives are used to buffer the ripple, resulting in significantly increased volume and cost. This article for the first time proposes active power decoupling (APD) for the SST and a predictive direct DC-link control method, using a current-source single-stage SST as an example. An electrolytic capacitor-less buffer port is used to absorb the ripple, which tolerates up to a 30% voltage ripple for small capacitance. The APD SST control is challenging. First, the current-source SST realizes isolation, DC link, and multiport in a single stage. Second, different from conventional SSTs or APD converters, the low-inertia DC link in this SST has a 40% switching ripple, which is difficult to stabilize. To address the control challenge, a direct DC-link control architecture and a predictive control method are proposed. Simulation and experimental results verify the proposed control method on an MV SiC modular soft-switching solid-state transformer (M-S4T) prototype. Here, the proposed APD reduces the SST volume by 53.8%. Importantly, the proposed concept is not limited to the M-S4T but is generic to other SSTs or APD converters.
14 SOLAR ENERGY↗
Development of a Modeling Framework to Support Control Investigations of Sailcraft Missions A First Cut: ABLE Sailcraft Dynamics Model
Solar Sailcraft, the stuff of dreams of the H.G. Wells generation, is now a rapidly maturing reality. The promise of unlimited propulsive power by harnessing stellar radiation is close to realization. Currently, efforts are underway to build, prototype and test two configurations. These sails are designed to meet a 20m sail requirement, under guidance of the In-Space Propulsion (ISP) technology program office at MSFC. While these sails will not fly , they are the first steps in improving our understanding of the processes and phenomena at work. As part of the New Millennium Program (NMP) the ST9 technology validation mission hopes to launch and fly a solar sail by 2010 or sooner. Though the Solar Sail community has been studying and validating various concepts over two decades, it was not until recent breakthroughs in structural and material technology, has made possible to build sails that could be launched. With real sails that can be tested (albeit under earth conditions), the real task of engineering a viable spacecraft has finally commenced. Since it is not possible to accurately or practically recreate the actual operating conditions of the sailcraft (zero-G, vacuum and extremely low temperatures), much of the work has focused on developing accurate models that can be used to predict behavior in space, and for sails that are 6-10 times the size of currently existing sails. Since these models can be validated only with real test data under "earth" conditions, the process of modeling and the identification of uncertainty due to model assumptions and scope need to be closely considered. Sailcraft models that exist currently, are primarily focused on detailed physical representations at the component level, these are intended to support prototyping efforts. System level models that cut across different sail configurations and control concepts while maintaining a consistent approach are non-existent. Much effort has been focused on the areas of thrust performance, solar radiation prediction, and sail membrane behavior vis-a-vis their reflective geometry, such as wrinkling/folding/furling as it pertains to thrust prediction. A parallel effort has been conducted on developing usable models for developing attitude control systems (ACS), for different sail configurations in different regimes. There has been very little by way of a system wide exploration of the impact of the various control schemes, thrust prediction models for different sail configurations being considered.
Sarathy, Sriprakash↗