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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 847 records · Page 47

Development of a precision, six-axis laboratory dynamometer

This paper describes the design, fabrication, test, and operation of a unique six axis force/torque dynamometer The specimen table used to hold components under test is supported in a full six axis kinematic mount. Support struts fabricated from high strength steel with special integral two axis flexures link the specimen table to the load cell transducers. Realtime force/torque coordinate transform, root mean squared calculation, and data averaging, and color six axis display with controllable scaling are provided by a specially programmed desktop computer. The extensive structural analysis and design optimization required to obtain a stiff, well damped, lightweight structure is described in detail. Geometric optimization of the kinematic mount and fabrication details of the struts are also described.

P. J. Champagne↗

Scalable Heterogeneous Execution of a Coupled-Cluster Model with Perturbative Triples

The CCSD(T) coupled-cluster model with perturbative triples is considered a gold standard for computational modeling of the correlated behavior of electrons in molecular systems. A fundamental constraint is the relatively small global-memory capacity in GPUs compared to the main-memory capacity on host nodes, necessitating relatively smaller tile sizes for high-dimensional tensor contractions in NWChem's GPU-accelerated implementation of the CCSD(T) method. A coordinated redesign is described to address this limitation and associated data movement overheads, including a novel fused GPU kernel for a set of tensor contractions, along with inter-node communication optimization and data caching. The new implementation of GPU-accelerated CCSD(T) improves overall performance by 3.4x. Finally, we discuss the trade-offs in using this fused algorithm on current and future supercomputing platforms.

Kim, Jinsung↗

Transient Stability Study of a Real-World Microgrid with 100% Renewables

This paper performs a transient stability study of a real-world microgrid that can operate with 100% renewables to better understand the stability and reliability of the microgrid under various dynamic scenarios. In particular, the operation of multiple grid-forming (GFM) and grid-following (GFL) inverters in such a power system is not well understood under dynamic operation conditions, such as islanding and black start; therefore, in this paper, an electromagnetic transient model of the microgrid is developed to investigate the stability of the system under various dynamic operating conditions and to identify potential reliability risks. The PSCAD/EMTDC simulation with the high-fidelity model provides helpful insights into the optimal operation modes of GFM and GFL inverters as well as the stability and reliability of the microgrid. It can also inform field deployment in terms of inverter control parameters and coordination as well as the expected performance of black start and unplanned islanding.

black start↗

Ensemble Learning Based Convex Approximation of Three-Phase Power Flow

Though the convex optimization has been widely used in power systems, it still cannot guarantee to yield a tight (accurate) solution to some problems. To mitigate this issue, this paper proposes an ensemble learning based convex approximation for alternating current (AC) power flow equations that differs from the existing convex relaxations. The proposed approach is based on three-phase quadratic power flow equations in rectangular coordinates. To develop this data-driven convex approximation of power flows, the polynomial regression (PR) is first deployed as a basic learner to fit convex relationships between the independent and dependent variables. Then, ensemble learning algorithms such as gradient boosting (GB) and bagging are introduced to combine learners to boost model performance. Based on the learned convex approximation of power flow, optimal power flow (OPF) is formulated as a convex quadratic programming problem. The simulation results on IEEE standard cases of both balanced and unbalanced systems show that, in the context of solving OPF, the proposed data-driven convex approximation outperforms the conventional semi-definite programming (SDP) relaxation in both accuracy and computational efficiency, especially in the cases that the conventional SDP relaxation fails

Convex approximation↗

Optimal Orbital Selection for Full Configuration Interaction (OptOrbFCI): Pursuing the Basis Set Limit under a Budget

Full configuration interaction (FCI) solvers are limited to small basis sets due to their expensive computational costs. An optimal orbital selection for FCI (OptOrbFCI) is proposed to boost the power of existing FCI solvers to pursue the basis set limit under a computational budget. The optimization problem coincides with that of the complete active space SCF method (CASSCF), while OptOrbFCI is algorithmically quite different. OptOrbFCI effectively finds an optimal rotation matrix via solving a constrained optimization problem directly to compress the orbitals of large basis sets to one with a manageable size, conducts FCI calculations only on rotated orbital sets, and produces a variational ground-state energy and its wave function. Coupled with coordinate descent full configuration interaction (CDFCI), we demonstrate the efficiency and accuracy of the method on the carbon dimer and nitrogen dimer under basis sets up to cc-pV5Z. We also benchmark the binding curve of the nitrogen dimer under the cc-pVQZ basis set with 28 selected orbitals, which provide consistently lower ground-state energies than the FCI results under the cc-pVDZ basis set. Furthermore, the dissociation energy in this case is found to be of higher accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optimizing Information Automation Using a New Method Based on System-Theoretic Process Analysis: Tool Development and Method Evaluation

This report is an update to a prior report that describes progress and findings for a program of research supporting the design and optimization of information automation systems for nuclear power plants. Much of the domestic nuclear fleet is currently focused on modernizing technologies and processes, including transitioning toward digitalization in the control room and throughout the plant, along with a greater interest in the use of automation, artificial intelligence, robotics, and other emerging technologies. While there are significant opportunities to apply these technologies toward greater plant safety, efficiency, and overall cost-effectiveness, optimizing their design and avoiding potential safety and performance risks depends on ensuring that human performance-related organizational and technical design issues are identified and addressed early in the design process. This report describes modeling tools and techniques, based on sociotechnical systems theory, to support these design goals and their application in the current research effort. The report is primarily intended for senior nuclear energy stakeholders, including regulators, corporate management, and senior plant management. We have developed and employed a method to design an optimized information automation ecosystem (IAE) based on the systems-theoretic constructs underlying sociotechnical systems theory in general and the Systems-Theoretic Accident Modeling and Processes (STAMP) approach in particular. We argue that an IAE can be modeled as an interactive information control system whose behavior can be understood in terms of dynamic control, feedback, and communication relationships amongst the system’s technical and organizational components. We have employed two STAMP-based tools in this effort. The first is Causal Analysis based on STAMP (CAST), an accident and incident analysis technique that was used to examine a performance- and safety-related incident at an industry partner’s plant involving the unintentional activation of an emergency diesel generator. This analysis provided insight into the behavior of the plant’s current information control structure within the context of a specific, significant event. The second tool is Systems Theoretic Process Analysis (STPA) which is a proactive risk analysis tool used to examine existing and potential, planned sociotechnical systems. STPA was used to identify risk factors in the current design of a generic nuclear power plant (NPP) preventive maintenance system. Our analyses focused on identifying near-term system improvements and longer-term design requirements for an optimized IAE system. CAST analysis findings indicate an important underlying contributor to the incident under investigation, and a significant risk to information automation system performance, was perceived time and schedule pressure, which exposed weaknesses in interdepartmental coordination between and within responsible plant organizations and challenged the resilience of established plant processes, until a human caused the eventual event. These findings are discussed in terms of their risk to overall system performance and their implications for information automation system resilience and brittleness. STPA findings exposed several areas of concern in the design of current preventive maintenance systems. We also present two preliminary information automation models. The proactive issue resolution (PIR) model is a test case of an information automation concept with significant near-term potential for application and subsequent reduction in significant plant events. The IAE model is a more general representation of a broader, plantwide information automation system and represents an end-state vision for our work. From our results, we have generated an initial set of preliminary system-level requirements and safety constraints for these models. We have also focused on early development of easy to learn, easy to use “transportable” tools for sociotechnical systems analysis. We intend these to be used by NPP personnel as a means of gaining reliable and relatively quick insight into (1) sociotechnical systems factors impacting incidents and accidents, (2) potential sociotechnical risk factors in existing or planned system designs, and (3) potential weaknesses in a system’s safety and/or information control structure. We conclude the report with a set of summary recommendations, a discussion of planned and potential follow-on research and development, and a draft list of system-level requirements and safety constraints for optimized information automation systems.

99 GENERAL AND MISCELLANEOUS↗

Spatial Optimization of Multiscale Biorefinery Deployment for a Diversified Bioeconomy in the United States

Strategic biorefinery siting is critical for a diversified bioeconomy, yet industry, policy, and research often focus on either large-scale biofuel plants or smaller-scale specialty bioproduct facilities, with limited coordination across scales. We address this gap by modeling biorefinery deployment spanning a 28-fold difference in capacity. We developed an open-source, spatially explicit framework integrating techno-economic analysis with logistics and refinery cost surrogate models to evaluate multiscale miscanthus-derived biorefineries across the rainfed U.S. for the production of ethanol, succinic acid, lactic acid, potassium sorbate, and acrylic acid. Overall costs change little as feedstock density increases, while transport distances decrease by ∼30 to 67% (∼100 km) and siting flexibility improves. Specifically, a 5-fold feedstock density increase (2% to 10% of suitable land) reduces minimum selling prices by <10% (e.g., 0.27 USD·gal –1 for ethanol). This limited economic sensitivity suggests dense planting is not required for competitive deployment, particularly for smaller-scale facilities. Representing collection areas as irregular rather than circular expands the feasible space under low-density scenarios. While large-scale refineries anchor regional supply chains, smaller facilities retain spatial flexibility even when large refineries are established. These findings highlight the importance of spatial representation and multiscale coordination for robust, regionally tailored biomanufacturing networks to advance renewable carbon integration without extensive land conversion.

biorefinery siting↗

Effect of modeled time horizon on quantifying the need for long-duration storage

Long-Duration Energy Storage (LDES) has gained interest due to its key role in attaining a decarbonized, low-cost, and stable grid driven by variable renewable electricity (VRE). Currently, there is a wide range of LDES technologies being developed to provide electricity with 8+ hours of consecutive discharge. However, current capacity expansion models used in long-term planning processes rarely consider low cost LDES as a candidate technology. If they do, the storage balancing horizon (SBH) of the model usually only considers non-consecutive 1-day periods that do not capture the potential of LDES to shift energy across multiple days or even seasons. Addressing these limitations in existing models, this work explores the ways in which the optimal energy storage changes when increasing the number of consecutive days in the SBH and how these changes will impact planners who are determining the future roles of energy storage. Our analysis uses SWITCH, an open-source capacity expansion model with a high spatial resolution for the entire Western Electricity Coordinating Council (WECC) in a zero-carbon scenario in 2050. We find that the number of consecutive days in the SBH changes both the total selected power and energy capacity of LDES when storage energy and power capacity overnight costs are $\$$13 USD/kWh (or less) and $113 USD/kW, respectively. We also find that the amount of required energy in storage to drive a future VRE-driven WECC grid ranges from 2.5 TWh to 16.0 TWh depending on the length of the SBH. The optimal storage duration (energy to power ratio) we obtain ranges from 10 h to 620 h among all the scenarios. Furthermore, depending on the storage cost assumption, we observe different charge/discharge patterns when varying the length of the SBH. Given our results, we anticipate that as more LDES technologies become commercially available, it will be critical to increase the length of the SBH to fully capture the benefits of LDES assets in long-term planning processes of high VRE-driven grids.

42 ENGINEERING↗

Engineering Single-Atom Cobalt Catalysts toward Improved Electrocatalysis

In this paper, the development of cost-effective catalysts to replace noble metal is attracting increasing interests in many fields of catalysis and energy, and intensive efforts are focused on the integration of transition-metal sites in carbon as noble-metal-free candidates. Recently, the discovery of single-atom dispersed catalyst (SAC) provides a new frontier in heterogeneous catalysis. However, the electrocatalytic application of SAC is still subject to several theoretical and experimental limitations. Further advances depend on a better design of SAC through optimizing its interaction with adsorbates during catalysis. Here, distinctive from previous studies, favorable 3d electronic occupation and enhanced metal-adsorbates interactions in single-atom centers via the construction of nonplanar coordination is achieved, which is confirmed by advanced X-ray spectroscopic and electrochemical studies. The as-designed atomically dispersed cobalt sites within nonplanar coordination show significantly improved catalytic activity and selectivity toward the oxygen reduction reaction, approaching the benchmark Pt-based catalysts. More importantly, the illustration of the active sites in SAC indicates metal-natured catalytic sites and a media-dependent catalytic pathway. Achieving structural and electronic engineering on SAC that promotes its catalytic performances provides a paradigm to bridge the gap between single-atom catalysts design and electrocatalytic applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Improving photovoltaic hosting capacity of distribution networks with coordinated inverter control: A case study of the EPRI J1 feeder

Abstract Adding photovoltaic (PV) systems in distribution networks, while desirable for reducing the carbon footprint, can lead to voltage violations under high solar‐low load conditions. The inability of traditional volt‐VAr control in eliminating all the violations is also well‐known. This article presents a novel coordinated inverter control methodology that leverages system‐wide situational awareness to significantly improve hosting capacity (HC). The methodology employs a real‐time voltage‐reactive power (VQ) sensitivity matrix in an iterative linear optimizer to calculate the minimum reactive power intervention from PV inverters needed for mitigating over‐voltage without resorting to active power curtailing or requiring step voltage regulator setting changes. The algorithm is validated using the EPRI J1 feeder under an extensive set of realistic use cases and is shown to provide 3x improvement in HC under all scenarios.

Dalal, Dhaval [School of Electrical, Computer, and↗

Packetized Energy Management: Coordinating Transmission and Distribution (Final Report)

The project Packetized Energy Management (PEM): Coordinating Transmission and Distribution was part of the ARPA-E NODES program from 2015 to 2023. The high-level goal of the project was to develop and demonstrate novel, scalable, and impactful technologies related to the coordination of networked distributed energy resources (DERs). By demonstrating responsive means by which fleets of DERs could be coordinated to enhance grid operation and reliability, the U.S. could accelerate renewable integration and electrification efforts and meet decarbonization goals.

25 ENERGY STORAGE↗

Advanced HVAC Humidity Control for Hot-Humid Climates

During this project we develop and validate a cost-effective, integrated control solution to improve humidity control and comfort for energy-efficient homes in hot-humid climates. This study focuses on developing a strategy that is effective, field tested, and practical for builders to install with minimal disruption to standard practices. A successful solution would simplify the transition to high-performance humidity control and be the basis for design and installation guidance. By relying on the central system as a starting point, the strategy employed minimizes system complexity and cost for builders, while improving comfort and operating cost for homeowners. The solution strategy was to coordinate the cooling, dehumidification, and ventilation functions of central, ducted HVAC systems to better control indoor humidity, improve occupant thermal comfort, and capture energy savings. The primary strategic goals were to: (1) optimize dehumidification by the central air-conditioning system, particularly during part-load conditions, using conventional equipment with modified control settings and lower system airflows; (2) maximize ventilation during heating/cooling on-cycles, to “bank” and condition outdoor ventilation air, and minimize ventilation during off-cycles; (3) quantify the effectiveness and energy impact of the dehumidification and ventilation strategies, while identifying a metric that would be useful to evaluate latent effectiveness. For the test houses in our study, located in Richmond Hill, Georgia; Houston, Texas; and Monroe, Louisiana we observed: (1) the indoor humidity did not exceed 60% RH during the monitored cooling season for 99% of the time in Richmond Hill, 96% of the time in Houston, and 90% of the time in Monroe; (2) the dehumidification strategy improved the steady-state latent capacity of the HVAC system at design conditions by 16% to 49% at the Houston test house and by 28% to 71% at the Monroe test house, depending on which mode the system was operating in; and (3) the good results at the test houses were primarily due to the amount of time the air-conditioning system operated in ramping or dehumidification modes, or both, particularly during the early cooling season. This study demonstrates that air conditioners or heat pumps with a single-stage compressor can provide good humidity control without the need for a two-stage or variable-stage compressor system. The airflow and control settings for ramping and dehumidification modes are critical to control indoor humidity in hot-humid climates, particularly during part-load and shoulder season conditions. The dehumidification strategy used in this study did not jeopardize the mechanical reliability of the cooling equipment. The strategies used in this study are applicable across various equipment brands, models, and efficiency levels, and also applicable to a broad range of homes in hot-humid climates. Results will vary by specific equipment, location, and house configuration and construction.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Hybrid vision activities at NASA Johnson Space Center

NASA's Johnson Space Center in Houston, Texas, is active in several aspects of hybrid image processing. (The term hybrid image processing refers to a system that combines digital and photonic processing). The major thrusts are autonomous space operations such as planetary landing, servicing, and rendezvous and docking. By processing images in non-Cartesian geometries to achieve shift invariance to canonical distortions, researchers use certain aspects of the human visual system for machine vision. That technology flow is bidirectional; researchers are investigating the possible utility of video-rate coordinate transformations for human low-vision patients. Man-in-the-loop teleoperations are also supported by the use of video-rate image-coordinate transformations, as researchers plan to use bandwidth compression tailored to the varying spatial acuity of the human operator. Technological elements being developed in the program include upgraded spatial light modulators, real-time coordinate transformations in video imagery, synthetic filters that robustly allow estimation of object pose parameters, convolutionally blurred filters that have continuously selectable invariance to such image changes as magnification and rotation, and optimization of optical correlation done with spatial light modulators that have limited range and couple both phase and amplitude in their response.

Juday, Richard D.↗

A complete analytical solution for the inverse instantaneous kinematics of a spherical-revolute-spherical (7R) redundant manipulator

Using a method based upon resolving joint velocities using reciprocal screw quantities, compact analytical expressions are generated for the inverse solution of the joint rates of a seven revolute (spherical-revolute-spherical) manipulator. The method uses a sequential decomposition of screw coordinates to identify reciprocal screw quantities used in the resolution of a particular joint rate solution, and also to identify a Jacobian null-space basis used for the direct solution of optimal joint rates. The results of the screw decomposition are used to study special configurations of the manipulator, generating expressions for the inverse velocity solution for all non-singular configurations of the manipulator, and identifying singular configurations and their characteristics. Two functions are therefore served: a new general method for the solution of the inverse velocity problem is presented; and complete analytical expressions are derived for the resolution of the joint rates of a seven degree of freedom manipulator useful for telerobotic and industrial robotic application.

Podhorodeski, R. P.↗

On th meridional surface profile of the Gulf Stream at 55 deg W

Nine-month records from nine inverted echo sounders (IESs) are analyzed to describe the mean baroclinic Gulf Stream at 55 deg W. IES acoustic travel times are converted to thermocline depth which is optimally interpolated. Kinematic and dynamic parameters (Gulf Stream meridional position, velocity, and vorticity) are calculated. Primary Gulf Stream variabiltiy is attributed to meandering and and changes in direction. A mean, stream-coordinate (relative to Gulf Stream instantaneous position and direction) meridional profile is derived and compared with results presented by other investigators. The mean velocity is estimated at 0.84 m/s directed 14 deg to the right eastward, and the thermocline (12 c) drops 657 m (north to south), corresponding to a baroclinic rise of the surface of 0.87 m. The effect of Gulf Stream curvature on temporal mean profiles is found to be unimportant and of minimal importance overall. The derived, downstream current profile is well represented by a Gaussian function and is about 190 km wide where it crosses zero. Surface baroclinic transport is estimated to be 8.5 x 10(exp 4) sq m/s, and maximum shear (flanking the maximum) is 1.2 x 10(exp -5). Results compare well with other in situ observational results from the same time period. On the other hand, analyses (by others) of concurrent satellite altimetry (Geosat) suggest a considerable narrower, more intense mean Gulf Stream.

Hallock, Zachariah R.↗

Resolving Off-Nominal Situations in Schedule-Based Terminal Area Operations: Results from a Human-in-the-Loop Simulation

A recent human-in-the-loop simulation in the Airspace Operations Laboratory (AOL) at NASA's Ames Research Center investigated the robustness of Controller-Managed Spacing (CMS) operations. CMS refers to AOL-developed controller tools and procedures for enabling arrivals to conduct efficient Optimized Profile Descents with sustained high throughput. The simulation provided a rich data set for examining how a traffic management supervisor and terminal-area controller participants used the CMS tools and coordinated to respond to off-nominal events. This paper proposes quantitative measures for characterizing the participants responses. Case studies of go-around events, replicated during the simulation, provide insights into the strategies employed and the role the CMS tools played in supporting them.

Mercer, Joey↗

Transient Stability Study of a Real-World Microgrid with 100% Renewables: Preprint

This paper performs a transient stability study of a real-world microgrid with 100% renewables to fully understand the stability and reliability of the microgrid under various dynamic scenarios. In particular, the operation of multiple grid-forming (GFM) and grid-following (GFL) inverters in such a power system is not well understood under dynamic operation conditions, such as islanding and black start; therefore, in this paper, the full-scale electromagnetic transient modeling of the microgrid is developed to investigate the stability of the system under various dynamic operating conditions and to identify potential reliability risks. The PSCAD/EMTDC simulation with the high-fidelity model provides helpful insights into the optimal operation modes of GFM and GFL inverters as well as the stability and reliability of the microgrid, which gives good references for the field deployment in terms of inverter configuration and coordination as well as the capabilities of black start and unplanned islanding.

100% renewable microgrid↗

Mitigating Cascading Outages in Severe Weather Using Simulation-Based Optimization

Severe weather events can trigger cascading power outages and lead to significant losses. In this work, we investigate cascading outage mitigation under severe weather conditions. Given day-ahead weather forecasts and component failure models, we aim to identify a set of power lines that can be hardened to minimize the expected impact of potential cascading outages. Since the expected load shedding cannot be expressed as an explicit function of line hardening decisions and system states, we developed a cascading outage simulator to estimate the expected value of load shedding under various initial weather-related disruption scenarios generated using a weather forecast. To avoid massive enumeration of all possible combinations of line hardening decisions and reduce the simulation efforts, we employed an efficient simulation-based optimization approach that quickly identifies the (near) optimal line hardening decisions in the presence of both large simulation noises due to the highly variable initial disturbances and system states, and significant randomness in the subsequent cascades. Furthermore, the algorithm is also able to utilize parallel computing to dramatically reduce computation time to support decision making in preparation for severe weather conditions. We performed a case study on the Northeast Power Coordinating Council (NPCC) 140-bus system model to demonstrate that our approach can significantly improve power grid resilience to adverse weather events.

24 POWER TRANSMISSION AND DISTRIBUTION↗