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Grid-Scale Electricity Storage at Lowest Possible Cost Enabled by Pumped Heat Electricity Storage (Final Report)
Grid-scale energy storage technologies that can provide greater than 10 hours of electricity at full power address a critical need for full penetration of renewables on electricity grids worldwide, minimize renewable curtailment, and maximize grid security and reliability. Pumped Heat Energy Storage (PHES) systems can store energy thermally in any location at the low costs necessary for displacing fossil fuels, reducing foreign fuel imports, and reducing emissions to maintain the energy security of the United States. The award allowed Southwest Research Institute® (SwRI®) and Malta, Inc. (Malta) to advance the PHES concept to a proof-of-concept demonstration for a kW-scale system. The project focused on system operation and integration. The main project objectives were: 1. Address first implementation challenges 2. Explore system control strategies and operation 3. Translate lessons learned to the full-scale system Through these objectives the project completes a first demonstration of this technology and reduces the technical risk associated with a full-scale system.
MADWEC Techno-Economic Analysis: Cooperative Research and Development Final Report
The objective of this project was for the facility to conduct a techno-economic assessment of the Maximal Asymmetric Drag Wave Energy Converter (MADWEC), developed by the University of Massachusetts Dartmouth (UMass Dartmouth), used for powering remote monitoring and AUV charging systems compared to other existing power supply options. The assessment estimates capital expenditures (CapEx), operational expenditures (OpEx), and power performance for 18 scenarios with the purpose of identifying key cost drivers, comparing total system cost, and comparing the power performance of the power supply options in terms of required installed capacity and estimated theoretical annual energy performance. The scenarios include two end-uses: (1) AUV charging and (2) offshore remote monitoring); three power sources: (1) MADWEC), (2) photovoltaic (PV) solar buoy, (3) and traditional battery swapping); and three locations; (1) nearshore, (2) far-offshore, and (3) high-latitude). In addition, other project goals included developing high level installation, operation, and maintenance plans for each scenario.
Seven years of IUE observations of the BL Lacertae object PKS 2155-304
Over 50 IUE spectra of the brightest known BL Lac object at ultraviolet wavelengths, PKS 2155-304, were reanalyzed using Gaussian extraction techniques that maximize the signal-to-noise. The ultraviolet continuum of PKS 2155-304 is well fitted by a power law model Fv varies as V sup-alpha, with an average spectral index for the combined SWP-LWR-P fits of less than alpha greater than 0.89 + or - 0.11 (standard deviation). While the ultraviolet intensity of PKS 2155-304 varies by a factor of 2, the spectral index changes very little and is uncorrelated with intensity. Timescales for ultraviolet variability are as short as 10 days. In one case, a well-matched pair of IUE images was obtained nearly simultaneously with a very soft X-ray measurement; the combined spectra clearly show a steepening between the ultraviolet and soft X-ray bands. The relevance of these findings to jet models and accretion models is discussed.
Avionics for a Small Robotic Inspection Spacecraft
A report describes the tentative design of the avionics of the Mini-AERCam -- a proposed 7.5-in. (approximately 19-cm)-diameter spacecraft that would contain three digital video cameras to be used in visual inspection of the exterior of a larger spacecraft (a space shuttle or the International Space Station). The Mini-AERCam would maneuver by use of its own miniature thrusters under radio control by astronauts inside the larger spacecraft. The design of the Mini-AERCam avionics is subject to a number of constraints, most of which can be summarized as severely competing requirements to maximize radiation hardness and maneuvering, image-acquisition, and data-communication capabilities while minimizing cost, size, and power consumption. The report discusses the design constraints, the engineering approach to satisfying the constraints, and the resulting iterations of the design. The report places special emphasis on the design of a flight computer that would (1) acquire position and orientation data from a Global Positioning System receiver and a microelectromechanical gyroscope, respectively; (2) perform all flight-control (including thruster-control) computations in real time; and (3) control video, tracking, power, and illumination systems.
Exploring Li-Air Batteries for High Specific Energy and High Power Applications: A Simulation Study
Commercialization of lithium-air batteries face many challenges, such as electrolyte decomposition, short cycle life, low energy efficiency, low power density, etc. However, commercialization of Li-air batteries for mass sensitive applications such as electric vehicles, portable power source, and drones is more challenging due to additional constraints of safety, electrolyte evaporation, high specific energy requirements, and reliable discharge times. In this presentation, we will present our finite element simulation results comparing Li-O2 and Li-air batteries using power density, energy density, specific power, and discharge times as metrics to evaluate different electrolytes and electrode geometry to reduce total mass and maximize discharge current. We use a finite element model and a discharge product model developed in which is based on porous electrode and concentrated electrolyte theories and the discharge product is modeled using quantum tunneling; for reaction kinetics and oxygen diffusion, an improved model was used. The electrolyte properties such as ion conductivity and ion diffusion were obtained from Molecular Dynamics (MD) simulations while the other parameters for the finite element model were calibrated to match experiments at high discharge current densities (>1.5 mA/cm2). The mass densities of different electrolytes were computed using MD simulations as well. For this presentation, we examine the practical electrochemical mass of a system at different current ratings, the sensitivity of mass to the use of ambient air as compared to pure oxygen as well as the electrolyte, which affects maximum current density and the total mass associated with the electrolyte (which includes the mass of additional components), and, the optimization of battery geometry for total discharge time, average discharge voltage, maximum discharge current, and minimum electrochemical mass.
Optimization, Design, and Demonstration of 1 kW Stirling Controller Using Capacitor-based Power Factor Correction
Free-piston Stirling convertors provide efficient, reliable thermal to electric power conversion, provided they are paired with a reliable controller. This paper outlines work underway on design concepts for kilowatt-class controllers. Using passive power factor correction (PFC) this design explores the possibility of reducing programmatic risk through system simplification. Efficiency is maximized through incorporating wide-bandgap gallium nitride (GaN) switches, and passive PFC volume is minimized through the use of polymer multi-layer capacitors. This work is aimed at exploring new approaches for future Stirling controllers.
Development of a low cost, low maintenance Maximal Asymmetric Drag Wave Energy Converter (MADWEC)
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MoRE-Brain: Routed Mixture of Experts for Interpretable and Generalizable Cross-Subject fMRI Visual Decoding
Decoding visual experiences from fMRI offers a powerful avenue to understand human perception and develop advanced brain-computer interfaces. However, current progress often prioritizes maximizing reconstruction fidelity while overlooking interpretability, an essential aspect for deriving neuroscientific insight. To address this gap, we propose MoRE-Brain, a neuro-inspired framework designed for high-fidelity, adaptable, and interpretable visual reconstruction. MoRE-Brain uniquely employs a hierarchical Mixture-of-Experts architecture where distinct experts process fMRI signals from functionally related voxel groups, mimicking specialized brain networks. The experts are first trained to encode fMRI into the frozen CLIP space. A finetuned diffusion model then synthesizes images, guided by expert outputs through a novel dual-stage routing mechanism that dynamically weighs expert contributions across the diffusion process. MoRE-Brain offers three main advancements: First, it introduces a novel Mixture-of-Experts architecture grounded in brain network principles for neuro-decoding. Second, it achieves efficient cross-subject generalization by sharing core expert networks while adapting only subject-specific routers. Third, it provides enhanced mechanistic insight, as the explicit routing reveals precisely how different modeled brain regions shape the semantic and spatial attributes of the reconstructed image. Extensive experiments validate MoRE-Brain’s high reconstruction fidelity, with bottleneck analyses further demonstrating its effective utilization of fMRI signals, distinguishing genuine neural decoding from over-reliance on generative priors. Consequently, MoRE-Brain marks a substantial advance towards more generalizable and interpretable fMRI-based visual decoding.
Bipolar Nickel-hydrogen Batteries for Aerospace Applications
A bipolar nickel-hydrogen battery which effectively addresses all key requirements for a spacecraft power system, including long-term reliability and low mass, is discussed. The design of this battery is discussed in the context of system requirements and nickel-hydrogen battery technology in general. To achieve the ultimate goal of an aerospace application of a bipolar Ni-H2 battery several objectives must be met in the design and development of the system. These objectives include: maximization of reliability and life; high specific energy and energy density; reasonable cost of manufacture, test, and integration; and ease in scaling for growth in power requirements. These basic objectives translate into a number of specific design requirements, which are discussed.
Influence of Ordered Mesoporous Oxides in Plasma-Assisted Ammonia Synthesis
Widespread implementation of dielectric barrier discharge (DBD)-assisted NH 3 synthesis, a nascent technology operating under sustainable, ambient conditions, is hindered by low energy yields due to, in part, poor fundamental understanding. Porous oxides used to support metal nanoparticle catalysts have shown significant energy yield contributions for DBD-assisted NH 3 synthesis even without metal. Using an AC-powered, coaxial, single-stage reactor at 16 kV with equimolar (N 2 /H 2 ) feed, we measured NH 3 synthesis rates in the presence of different nonordered oxides, ordered SiO 2 structures (SBA-15 and MCM-41), and ordered Al-incorporated analogues (γ-Al 2 O 3 -coated with varying Al-loadings and Al-substitution, respectively: Al 2 O 3 -SBA-15 and Al-MCM-41). We systematically quantified NH 3 energy yield dependence on pore structures and material identities (i.e., ordered pores and Al incorporation) known to facilitate higher DBD-assisted NH 3 synthesis rates. SBA-15 displayed a higher steady-state energy yield than MCM-41, indicating that framework type is a crucial factor, with both ordered porous systems outperforming fumed SiO 2 . 10 wt % Al maximized in situ NH 3 uptake among the various Al loadings, exhibiting a higher steady-state energy yield and similar power to SBA-15. However, Al-MCM-41 had a similar steady-state energy yield and lower power than MCM-41, likely due to the extended γ-Al 2 O 3 surface that has a dielectric constant higher than that of SiO 2 . Both Al-incorporated analogues benefit from surface acid sites that can adsorb NH 3 in situ, resulting in higher overall NH 3 energy yields than that of their parent ordered SiO 2 . Al 2 O 3 -SBA-15 shielded more NH 3 than Al-MCM-41, likely due to a higher acid site density than the acid site identity. Furthermore, Al incorporation via γ-Al 2 O 3 coating more successfully improves the NH 3 energy yield; together with the high-performing ordered framework, these analogues are potential metal catalyst supports with promising energy yields for DBD-assisted synthesis of NH 3 and other chemicals.
Fabrication and Characterization of Single-Particle Compacts
The programmatic objective of the advanced low enriched uranium (aLEU) fuel Project within the Office of Nonproliferation Research and Development (NA-22) is to advance the development of nuclear reactor designs, fuel materials, and fabrication technologies capable of meeting a number of challenging customer requirements, including reactor stability, extended lifetime, and power density without refueling, while using only low-enriched uranium (i.e., less than 20% enrichment of 235 U). The tandem requirements of delivering sufficient power density and maintaining fuel performance over the course of a multidecade fuel lifetime tightly constrain the field of potential fuel options. Monolithic fuel forms (e.g., fuel pellets) provide maximized density of fissile material, but they may face challenges in maintaining their structure and performance over the long reactor lifetimes envisioned in this program. Dispersion fuel forms with an inert matrix provide enhanced long-term stability but sacrifice fissile material density, and they may not provide sufficient power density over the reactor lifetime with the limit of low enrichment.
Exploring the design space of PV-plus-battery system configurations under evolving grid conditions
In this study, we explore how the energy and capacity values of coupled systems comprising solar photovoltaic arrays and battery storage (PV-plus-battery systems) could evolve over time based on the evolution of the bulk power system. Using a price-taker model with simulated hourly energy and capacity prices projected from the present to 2050, we simulate the revenue-maximizing dispatch of a range of DC-coupled PV-plus-battery configurations in three locations in the United States. These configurations are defined by the inverter loading ratio (ILR, the ratio of the PV array capacity to the inverter capacity, which we vary from 1.4 to 2.6) and the battery-inverter ratio (BIR, the ratio of the battery power capacity to the inverter capacity, which we vary from 0.25 to 1.0). Based on each configuration's total value, we estimate the breakeven costs needed to justify each incremental increase in ILR (holding BIR constant) or BIR (holding ILR constant). We find that, in a future with low-cost renewable energy technologies, PV-plus-battery system ILRs can be economically increased to around 2.0-2.4 at a BIR of 1.0, depending on solar resource. Our results indicate that a likely evolution of PV-plus-battery system design will be increasingly greater battery power capacity to mitigate the declining PV capacity value, which will, in turn, enable increasingly higher ILRs to further increase energy value. The extent to which PV-plus-systems will be deployed with increasingly higher ILRs depends primarily on whether PV cost declines outpace declining value and increasing curtailment over time.
Utilization of Machine Learning Techniques for Managing the Tracking and Data Relay Satellite Constellation
National Aeronautics and Space Administration’s (NASA) Goddard Space Flight Center (GSFC) operates a constellation of ten geosynchronous Tracking and Data Relay Satellites (TDRS). The TDRS constellation consists of multiple geosynchronous communication relay satellites located around the equator so they can provide continual coverage of any mission in low earth orbit. The TDRS are located primarily in three oceanic regions around the earth. NASA’s White Sands Complex provides the ground communication support for TDRS located over the Atlantic and Pacific Oceans. Another TDRS ground station in Guam supports the TDRS over the Indian Ocean. With these satellites the TDRS network can provide continuous coverage of satellites in low-earth orbit. The NASA Space Network (SN) project office at GSFC manages the constellation of spacecraft. Major customers of the TDRS constellation include, but are not limited to, the International Space Station and the Hubble Space Telescope. The TDRS constellation has three generations of satellites and has been active for over 30 years providing reliable communication links between customer satellites and corresponding ground stations. However, one of the major concerns for TDRS, and in any space mission, is to ensure the health and safety of the spacecraft. Generally, engineers use telemetry data to monitor and analyze the performance and state of health of the spacecraft. Telemetry data contains hundreds of parameters that monitor each important component in the spacecraft, which can be utilized to recognize and characterize the behavior of the spacecraft. Each parameter contains considerable information to represent time-dependent properties of each spacecraft subsystem and component. During the entire life of a TDRS spacecraft, thousands of gigabytes of telemetry data are transmitted in real-time from the spacecraft to the ground station at the White Sands Complex in Las Cruces, New Mexico, and recorded as historical data sets for engineers to process and analyze the events that occurred on-orbit. These parameters contain the function of multiple spacecraft subsystems, such as the attitude control system (ACS), Thermal, Electrical Power Subsystem (EPS), etc. . The first and second generations have exceeded their required lifetime and NASA is keen to manage these spacecrafts carefully in order to maximize the remaining life using the spacecraft telemetry. The challenge is to know when the risk of losing a spacecraft in geosynchronous orbit exceeds the benefit of continued operations for customer support. In the TDRS fleet, the EPS is the most critical subsystem related to spacecraft operations. Failure of the EPS would strand a spacecraft in geosynchronous orbit. Since EPS provides power to the spacecraft, component failures ultimately lead to the inability to support the spacecraft loads and the communications payload. For instance, TDRS-8 has several anomalies in EPS including the Bus Voltage Limiter (BVL) shunt current, solar array loss of circuits, and failed battery cells. Any of these anomalies can cause critical issues to the spacecraft. Therefore, developing a system to analyze and perform early detection of a potential anomaly is an important issue in telemetry data analysis. In recent years, Telemetry Mining (TM) has been proposed to process telemetry data by using Data Mining (DM) techniques such as classification, clustering, regression and anomaly detection. Anomaly detection, also known as outlier detection, has been widely used in many data mining areas such as remote sensing, medical data processing and digital image processing. The goal of anomaly detection is to detect abnormal data, which contains a relatively low probability of occurrence among the entire data set. Early detection of anomalies is one of the most significant issues in managing the spacecraft configuration. If anomalies can be detected early enough, then the redundant resources can be used to extend the life of the operational spacecraft. We present an unsupervised anomaly detection method to process the EPS data extracted from TDRS-8. This is different from traditional analytical methods, which use telemetry data to illustrate behavior and physical meaning of each spacecraft component. TM connects multiple parameters as a vector and then conducts data analysis on this high dimension telemetry vector. This method is looking at the properties of a high dimensional vector that is able to consider the relationship between different parameters in the anomaly detection problem. This kind of method performs much better than the traditional limit checking method. In addition, we propose a new approach of real-time anomaly detection to process telemetry data in real-time, which can then be applied to spacecraft monitoring with high reliability, low cost and high accuracy.
Optical Properties of Thin Film Molecular Mixtures
Thin films composed of molecular mixtures of metal and dielectric are being considered for use as solar selective coatings for a variety of space power applications. By controlling the degree of molecular mixing, the solar selective coatings can be tailored to have the combined properties of high solar absorptance, , and low infrared emittance, . On orbit, these combined properties would simultaneously maximize the amount of solar energy captured by the coating and minimize the amount of thermal energy radiated. Mini-satellites equipped with solar collectors coated with these cermet coatings may utilize the captured heat energy to power a heat engine to generate electricity, or to power a thermal bus that directs heat to remote regions of the spacecraft. Early work in this area identified the theoretical boundary conditions needed to operate a Carnot cycle in space, including the need for a solar concentrator, a solar selective coating at the heat inlet of the engine, and a radiator.1 A solar concentrator that can concentrate sunlight by a factor of 100 is ideal. At lower values, the temperature of the solar absorbing surface becomes too low for efficient heat engine operation, and at higher values, cavity type heat receivers become attractive. In designing the solar selective coating, the wavelength region yielding high solar absorptance must be separated from the wavelength region yielding low infrared emittance by establishing a sharp transition in optical properties. In particular, a sharp transition in reflectance is desired in the infrared to achieve the desired optical performance. For a heat engine operating at 450 C, a sharp transition at 1.8 micrometers is desired.2 The radiator completes the heat flow through the Carnot cycle.
Resistance exercise prevents plantar flexor deconditioning during bed rest
Because resistance exercise (REX) and unloading induce opposing neuromuscular adaptations, we tested the efficacy of REX against the effects of 14 d of bed rest unloading (BRU) on the plantar flexor muscle group. Sixteen men were randomly assigned to no exercise (NOE, N = 8) or REX (N = 8). REX performed 5 sets x 6-10 repetitions to failure of constant resistance concentric/eccentric plantar flexion every other day during BRU. One-repetition maximum (1RM) strength was tested on the training device. The angle-specific torque-velocity relationship across 5 velocities (0, 0.52, 1.05, 1.75, and 2.97 rad.s-1) and the full range-of-motion power-velocity relationship were assessed on a dynamometer. Torque-position analyses identified strength changes at shortened, neutral, and stretched muscle lengths. Concentric and eccentric contractile work were measured across ten repetitions at 1.05 rad.s-1. Maximal neural activation was measured by surface electromyography (EMG). 1RM decreased 9% in NOE and improved 11% in REX (P < 0.05). Concentric (0.52 and 1.05 rad.s-1), eccentric (0.52 and 2.97 rad.s-1), and isometric angle-specific torques decreased (P < 0.05) in NOE, averaging 18%, 17%, and 13%, respectively. Power dropped (P < 0.05) in NOE at three eccentric (21%) and two concentric (14%) velocities. REX protected angle-specific torque and average power at all velocities. Concentric and eccentric strength decreased at stretched (16%) and neutral (17%) muscle lengths (P < 0.05) in NOE while REX maintained or improved strength at all joint positions. Concentric (15%) and eccentric (11%) contractile work fell in NOE (P < 0.05) but not in REX. Maximal plantar flexor EMG did not change in either group. In summary, constant resistance concentric/eccentric REX completely prevented plantar flexor performance deconditioning induced by BRU. The reported benefits of REX should prove useful in prescribing exercise for astronauts in microgravity and for patients susceptible to functional decline during bed- or chair-bound hospital stays.
Demonstrating Advanced Nuclear Energy Solutions for Net Zero
Background/Objectives. The aggressive goals being set by nation states, communities, and private industry for decarbonization of grid electricity, industrial heat sources, and transportation around the world are imperative to mitigating the devastating effects that we are seeing from climate change. Although many of these goals focus on accomplishments by 2035 or 2050, the decisions that we make today won’t just impact the landscape of energy systems for the next 20 or 30 years—they will shape the world’s environment for centuries to come. That means that we can’t just focus on technologies that will get us to 2050, but technologies that will withstand our energy demands over that long-ranging future. Success will require us to utilize all of the clean energy resources that we have available to meet demands for electricity, heat, and steam, and we will need energy carriers such as hydrogen that do not emit additional greenhouse gases at the point of use. Nuclear energy, ranging from technologies in service today to advanced, higher temperature and modular systems that will be in service this decade, will provide a robust complement to renewable energy resources that operate variably. Researchers across the U.S. Department of Energy laboratory complex are working to advance multiple aspects of these clean energy solutions, with many focusing on integrated energy system solutions that leverage all available clean energy assets to meet wide-ranging energy demands. Approach/Activities. Nuclear energy is a proven, zero-emission option during operation that can provide consistent, dispatchable power to meet electricity demands while also providing high-quality heat that can meet energy demands beyond the electricity sector. Energy system design should seek to maximize these assets. As a dispatchable energy source with a small land utilization footprint, nuclear energy can be collocated with renewable resources, and the smaller systems that will be deployed this decade (ranging from a few megawatts to hundreds of megawatts) can be installed right where that energy is needed. Integrated nuclear and renewable systems will enhance power grid reliability and resilience, and they will help stabilize the grid through their increasingly flexible operation. Licensing, installation, and broad adoption of these advanced nuclear energy systems are expected to progress significantly in the 2020s, but this may be longer than desired by some stakeholders wishing to implement impactful clean energy decisions today. However, one must recall that nuclear energy systems will operate for 80 or more years, as is being demonstrated by current fleet nuclear systems. The nuclear community is extremely thorough in reviewing these systems with regard to safety and security; these efforts ensure that the deployed systems will continue to provide reliable, resilient energy over that operational lifetime. That investment of time up front will ensure that we can support energy demands over the centuries to come. While advanced nuclear technologies move through this process, communities and private industry may choose to install renewable generation systems that can later be coupled to the complementary nuclear systems as they become available—thus moving closer to the net zero goals in the near term. Choosing technologies and deployment configurations that allow small modular nuclear powerhouses to be added to these “energy parks” as they become available will ensure that advanced technologies can be readily adopted to support growing demands for clean energy. Results/Lessons Learned. The primary focus of integrated energy systems (IES) research is to assess the technical and economic potential of novel multi-input, multioutput solutions that are expected to enhance energy system flexibility, reliability, and resilience as we pursue a clean energy transition. Various energy applications and product streams beyond electricity are being evaluated, ranging from generation of potable water to production of hydrogen, fertilizers, synthetic fuels, and various chemicals. In early FY23 Idaho National Laboratory (INL) will commission thermal energy generation systems that emulate nuclear fission energy input using electric heating and will allow for integrated system testing with thermal energy storage, hydrogen production via high temperature electrolysis (HTE), and power systems hardware to demonstrate operation of a clean energy park within a microgrid or larger grid infrastructure, supporting up to 450 kW of heat input via electric heating and demonstrating operation of HTE systems at the multi-hundred kW scale. This presentation will highlight the wide array of RD&D being conducted at INL and partner laboratories to develop and deploy nuclear and renewable-based IES that will be key to achieving our net zero goals, including both computational and experimental demonstrations. By working with key collaborators in industry, analytical st
Supercharging simulation-based inference for Bayesian optimal experimental design
Abstract Bayesian optimal experimental design (BOED) seeks to maximize the expected information gain (EIG) of experiments. This requires a likelihood estimate, which in many settings is intractable. Simulation-based inference (SBI) provides powerful tools for this regime. However, existing work explicitly connecting SBI and BOED is restricted to a single contrastive EIG bound. We show that the EIG admits multiple formulations which can directly leverage modern SBI density estimators, encompassing neural posterior, likelihood, and ratio estimation. Building on this perspective, we define a novel EIG estimator using neural likelihood estimation. Further, we identify optimization as a key bottleneck of gradient based EIG maximization and show that a simple multi-start parallel gradient ascent procedure can substantially improve reliability and performance. With these innovations, our SBI-based BOED methods are able to match or outperform by up to 22% existing state-of-the-art approaches across standard BOED benchmarks.