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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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As renewables grow to meet both increased decarbonization and electrification goals, functionality such as grid-forming capability needs to be developed. Medium-voltage power electronic-enabled interfaces for renewables and as new devices within the grid themselves are an ideal platform for implementing these functionalities.
The overarching objective of this project was to develop a molecular-scale understanding of chemical interactions of the transuranic (TRU) elements with uranyl-based polyoxometalate nanoclusters (UPOMs). The specific goals that supported this overarching objective were to: (i) quantify TRU interactions with UPOMs as a function of TRU, carbonate, and UPOM concentration, pH, and temperature; (ii) examine the molecular-level bonding environment of TRU-UPOM complexes; and (iii) develop a rate expression capable of describing the sorption and reduction of TRU by UPOMs. The published literature suggests several potential interactions can occur in TRU-UPOM systems: (i) encapsulation of TRU and coordination with the internal ‘-yl’ oxygens of the UPOM, (ii) coordination of TRU with the external ‘-yl’ oxygens of the UPOM, and (iii) coordination of TRU with the bridging ligands (e.g., peroxo, hydroxo, oxalate) of the UPOM. The latter two may induce aggregation of the UPOMs. The concept of encapsulation is demonstrated by the X-ray diffraction structure of crystallized U 20 , which reveals a Na + cation under each pentagonal face (Sigmon et al., 2009). Computational modeling shows that, while the negative charge of U 20 is spread among all the oxygen atoms, the internal ‘-yl’ oxygens host the most negative charge (Miro and Bo, 2012). This negative charge is reduced through the complexation of the templating sodium ions in the interior of the UPOM. Furthermore, Nyman et al. (2011) shows that cesium can exit through the pentagonal window of U 28 in the aqueous phase, suggesting that the TRU elements, which are smaller than cesium, may be capable of entering a UPOM through these windows in an exchange reaction. Under this project, we focused on hafnium, neptunium, and plutonium interactions with UPOMs.
Abstract: The talk will focus on modeling capabilities supporting design and development of molten salt technologies and discuss path forward.
This poster is for the LDRD Poster Session held at INL. The intent is to highlight the intent of the project which was to develop a resilient communication capability for the WSComm waveform. The poster shows notional pictures of communications being inhibited by a low power transmitter such as one found in modern drones. It then highlights interference tolerance performance and notionally shows that replay attacks may impede the signal. By implementing Transmission Security (TRANSEC), one can protect the waveform from such attacks.
Advanced sensor capabilities for the simultaneous on-site detection of specific chemical, biological, and radiological/nuclear (CBRN) threats is important to significantly limit the risk of exposure to personnel and allow the rapid collection of essential scientific data and critical evidence. Commercially available sensor capabilities are generally complex, and/or require highly specific and ultra-sensitive methods that are often power demanding or require offsite post-analysis for positive detection, leaving personnel vulnerable. The goal of this project is to develop a portable sensor capable of simultaneously detecting CBRN signatures using a multiplexed Förster Resonance Energy Transfer (FRET) based sensor. FRET sensors are tailorable, specific, and highly dependent on the donor-acceptor distance. In this project, nanoparticles were functionalized with aptamers that were designed for the detection of methylphosphonate, a sarin metabolite. FRET was measured between quantum dot donors and dye and metal nanoparticle acceptors using optical spectroscopy.
This paper performs research on predicting Photovoltaic (PV) inverters reliability and lifetime based on thermal cycling. Thermal cycling is considered the most important stressors in an inverter system. In order to achieve this, a detailed electro-thermal model of the PV inverter will be developed along with their controllers capable of providing voltage support through reactive power. An in-house inverter was built, and a PV inverter model was developed to match the physical inverter. The PV inverter electrothermal model was validated for different ambient temperatures to match the in-house inverter hardware. The in-house inverter was placed inside a thermal chamber to emulate different ambient temperatures and their losses and temperature rises within the system were measured. After the validation of the model, a reduced order model of the inverter will be implemented to translate the mission profile of ambient temperature and solar irradiance into load profile of junction temperatures of the switches. The junction temperature data will be used to identify the reliability indices and hence predict the useful lifetime of the inverter system. Along with the model to predict useful lifetime of the system, the impact of reactive power on the overall reliability of the system will be studied. The key observation in this paper shows that lifetime of the inverter decreases as the operating power factor moves away from unity.
The Spent Fuel & Waste Science and Technology (SFWST) Campaign of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE), Office of Spent Fuel & Waste Disposition (SFWD) is conducting research and development (R&D) on geologic disposal of spent nuclear fuel (SNF) and high-level nuclear waste (HLW). A high priority for SFWST disposal R&D is to develop a disposal system modeling and analysis capability for evaluating disposal system performance for nuclear waste in geologic media. This report describes fiscal year (FY) 2022 accomplishments by the PFLOTRAN Development group of the SFWST Campaign. The mission of this group is to develop a geologic disposal system modeling capability for nuclear waste that can be used to probabilistically assess the performance of generic disposal concepts. In FY 2022, the PFLOTRAN development team made several advancements to our software infrastructure, code performance, and process modeling capabilities.
Here, the mission of the low aspect ratio spherical tokamak NSTX-U is to advance the physics basis and technical solutions required for optimizing the configuration of next-step steady-state tokamak fusion devices. NSTX-U will ultimately operate at up to 2 MA of plasma current and 1 T toroidal field on axis for 5 s, and has available up to 15 MW of neutral beam injection power at different tangency radii and 6 MW of high harmonic fast wave heating. With these capabilities NSTX-U will develop the physics understanding and control tools to ramp-up and sustain high performance fully non-inductive plasmas with large bootstrap fraction and enhanced confinement enabled via the low aspect ratio, high beta configuration. With its unique capabilities, NSTX-U research also supports ITER and other critical fusion development needs. Super-Alfvénic ions in beam-heated NSTX-U plasmas access energetic particle (EP) parameter space that is relevant for both α-heated conventional and low aspect ratio burning plasmas. NSTX-U can also generate very large target heat fluxes to test conventional and innovative plasma exhaust and plasma facing component solutions. This paper summarizes recent analysis, theory and modelling progress to advance the tokamak physics basis in the areas of macrostability and 3D fields, EP stability and fast ion transport, thermal transport and pedestal structure, boundary and plasma material interaction, RF heating, scenario optimization and real-time control.
This report documents the second phase of the critical experiment design process (CED-2) conducted as part of integral experiment request (IER) 304. The purpose of IER-304 is to develop a temperature-dependent critical experiment capability at the Sandia National Laboratories critical experiment facility using low-enriched uranium oxide fuel. Only a few benchmark quality critical experiments are currently available to validate criticality safety computational methods at temperatures other than room temperature. Recent advancements in computational techniques such as implementation of on-the-fly Doppler broadening techniques and advanced treatment of thermal scattering data necessitate the development of additional experimental capabilities in this area. The work described in this report developed representative configurations using 7uPCX and BUCCX fuels, analyzed the physics exercised by the different arrays, and analyzed the estimated experimental uncertainties. This report also scopes the information necessary for performing modifications to the reactor to accommodate operation at elevated and reduced temperatures.
One fundamental question underlying all living organisms is the need to understand their hierarchical organizations and physical changes with the necessary spatial and temporal resolutions under physiological or pathological conditions. This is a multi-scale challenge requiring imaging from sub-nanometers to micrometers in a cellular context. While individual imaging techniques are available, there is a critical need to integrate them into a workflow capability. Our objective is to develop an integrated multi-disciplinary and multi-scale bioimaging capability at Brookhaven National Laboratory (BNL). The capability expands BNL’s existing facility operation program in bioimaging and positions BNL in a leadership position in bioimaging research. The capability also addresses the grand challenges of the Department of Energy (DOE) science programs for national bioenergy sustainability and security.
Single-feed polymer extruders are widely used in large-format additive manufacturing (AM) systems; however, the increasing demand for multi-material functionality within a single part has driven significant innovation in this field. One approach involves robotic pick-and-place operations, while another explores mechanical switching of feed lines during extrusion. Although robotic pick-and-drop systems offer flexibility, they introduce longer layer times during material changes, which can negatively affect the structural integrity of the part. On the other hand, mechanical feed switching causes delays in material transitions, as the existing material must be flushed before the new material emerges from the nozzle. This poses particular challenges for smaller or more intricate parts. In this study we are developing a unique multiplexing extrusion system with core & sheath nozzle that combines two extruders via co-extrusion. This allows for a unique inside and outside inner-bead (i.e., within the same bead) multi-material capability. We believe that this technology will allow for combining neat and filled materials, ductile and stronger materials, and many other combinations to address the problems aforementioned above and disrupt the AM technology creating new opportunities and opening application areas.
This library builds a framework for defending ML models against adversarial attacks. The library will be developed at various stages leading to publication and software release at each stage. We employ tensor decomposition strategies as preprocessing stages for the first stage to provide robustness against the prominent adversarial noise. In the second stage, we develop a latent noise generator capable of generating novel adversarial noise that threatens the existing state-of-the-art defense strategy. In the third stage, we develop a UNSUP-GAN model, where the generator is trained to denoise against latent noise and most adversarial noises. This generator can provide a robust adversarial attack against any unseen attack.
Developing research in a time-at-temperature limit for fuel failure requires assessing both the material modeling and the thermal-hydraulic modeling capabilities. Predictions of post-CHF conditions have areas for development leveraging experiments, code coupling, and general model improvement.
The complex interdependencies of cyber systems (sensors and communications), physical grids and associated electricity market operations make protecting electric power grids a significant challenge. The energy sector is constantly under new, targeted, advanced and dangerous cyber-attacks that have the potential to result in the loss of human life. These threats are further exacerbated by our need to modernize the grid. One focus of cyber security research in smart grids is the securing of the SCADA system through advanced intrusion detection systems (IDS) and bad data detection algorithms in state estimation. These methods either require full knowledge of the system topology and parameters or fail to understand the physical behaviors under attack. WISP (Watching grid Infrastructure Stealthily through Proxies) is designed to provide additional protection to the power grid using only publicly available data. In particular, WISP exploits the spatio-temporal nature of the real time locational marginal prices (LMPs), in conjunction with other information such as bids, weather, outages and load data to analyze anomalous power pricing behaviors and then correlate those observations to localize regions of interest and identify potential cyber events. WISP is non-intrusive as the tool is deployed as a service in the Cloud or on premise and provides reliable information to system operators for enhanced situational awareness, without impeding energy delivery functions. The WISP technology comprises three modules: the data-driven anomaly detection core, the vulnerability and risk analysis and the root cause analysis. The data-driven anomaly detection core performs the tasks of feature selection, anomaly detection and attack region localization. The vulnerability and risk analysis module provides system level information of the vulnerable variables and times, assisting the operators in selecting monitoring and protection nodes. The root cause analysis module takes the detection results and identifies potential operational conditions that contribute to the detected anomalies. In Phase I, we have demonstrated the feasibility and effectiveness of WISP. We developed a realistic electricity market simulator capable of generating normal and attack market data under various operational conditions. We developed a series of cyber-attack detection and analysis algorithms and evaluated them under multiple data sources. Finally, we integrated all modules into an end-to-end software, providing functions for data management, data analytics and visualization. Specifically, we have achieved: (i) real-time data acceptance from external utility interfaces with >99% acceptance rate; (ii) high performance anomaly detection algorithms with >98% detection accuracy and <0.1% false alarm rate; and (iii) ultra-low computing delay <50 milliseconds. Additionally, our team developed algorithms to identify the vulnerable variables in electricity market operations and root cause analysis functions to identify major contributors to the price spikes. These ancillary modules are necessary when deploying WISP in real world industry environment. In Phase II, we have demonstrated the effectiveness of WISP software on realistic largescale power systems. We performed red team testing for the Phase I WISP software and identified software vulnerabilities and implemented corresponding mitigation solutions. We adapted the electricity market simulator for the Texas synthetic 2000-bus system and generated datasets for the false data injection attacks. We created database and visualization interfaces for the Texas system and the ISO New England system. We performed software optimization in terms of operation efficiency, computing speed and detection accuracy. Finally, we tested the software on the Texas system and the ISO New England system and evaluated the detection performance. Overall, we achieved above 89% detection rate, below 3% false alarm rate and below 37 seconds of end-to-end detection delay.
This paper seeks to introduce the latest design of the Extended Length Test Assembly–Cartridge Lead (ELTA-CL) with associated thermal-hydraulic (TH) assessment and related experiment activities to support the critical component development performed by the ELTA-CL team (Los Alamos National Laboratory, Westinghouse Electric Company, and the University of New Mexico). The goal of the ELTA-CL program is to develop and validate an experimental capability to perform irradiation experiments in the Versatile Test Reactor (VTR) addressing Lead Fast Reactor (LFR) technology gaps, in support of the commercial development of advanced lead-cooled fast reactor concepts. Through a design maturation process and parametric study, a conceptual design is proposed to meet the requirements for material and corrosion testing. Thermal-hydraulic characteristics for the conceptual design at desired operating conditions are assessed with systems-level (one-dimensional) and computational fluid dynamics (three-dimensional) simulations. Along with the conceptual design work, experimental activities for the development of critical components such as the pump and flowmeter are undertaken. From both the modeling study and the experimental results, the design requirements of the Phase 1 ELTA-CL (e.g., 500°C and 2 m/s) are achievable with the current conceptual design. Additional design improvements and safety assessments at both steady-state and transient conditions for the final ELTA-CL design will be pursued.
Assess the evolving integration potential of light-duty (LDV) and heavy-duty vehicle (HDV) technologies, fuels, and infrastructure and their contributions to lowering emissions and petroleum consumption. Leverage existing LDV and build HDV ParaChoice capability to conduct parametric analyses that explore the trade-space for key factors that influence consumer choice and technology, fuel and infrastructure development. ParaChoice provides the unique capability to examine tipping points and tradeoffs, and can help quantify the effects of and mitigate uncertainty introduced by data sources and assumptions.
Identification of metabolic engineering targets is a fundamental challenge in strain development programs. While high-throughput (HTP) genetic engineering methodologies capable of generating vast diversity are being developed at a rapid rate, a majority of industrially interesting molecules cannot be screened at sufficient throughput to leverage these techniques. We propose a workflow that couples HTP screening of common precursors (e.g., amino acids) that can be screened either directly or by artificial biosensors, with low-throughput targeted validation of the molecule of interest to uncover nonintuitive beneficial metabolic engineering targets and combinations hereof. Using this workflow, we identified several nonobvious novel targets for improving p-coumaric acid (p-CA) and L -DOPA production from two large 4k gRNA libraries each deregulating 1000 metabolic genes in the yeast Saccharomyces cerevisiae. We initially screened yeast cells transformed with gRNA library plasmids for individual regulatory targets improving the production of l-tyrosine-derived betaxanthins, identifying 30 targets that increased intracellular betaxanthin content 3.5–5.7 fold. Hereafter, we screened the targets individually in a high-producing p-CA strain, narrowing down the targets to six that increased the secreted titer by up to 15%. To investigate whether any of the six targets could be additively combined to improve p-CA production further, we created a gRNA multiplexing library and subjected it to our proposed coupled workflow. The combination of regulating PYC1 and NTH2 simultaneously resulted in the highest (threefold) improvement of the betaxanthin content, and an additive trend was also observed in the p-CA strain. Lastly, we tested the initial 30 targets in a L -DOPA producing strain, identifying 10 targets that increased the secreted titer by up to 89%, further validating our screening by proxy workflow. This coupled approach is useful for strain development in the absence of direct HTP screening assays for products of interest.
Successful widespread commercialization of electric vehicles is contingent upon development of safe high energy density batteries capable of long cycle life. Lithium metal affords the highest theoretical capacity (3,860 mAh/g) and lowest electrochemical potential (-3.04V vs SHE), which offers the highest specific energy density of anode materials today. While Li-ion batteries are capable of delivering energy densities of 400-600 Wh/kg, the development of lithium metal batteries such as Li-S and Li-air may boost this number up to 650 and 950 Wh/kg, respectively. However, significant progress towards the passivation of lithium metal must occur before the energy density benefit can be realized. Issues with lithium dendrite formation, anode volume expansion, and continuous solid electrolyte interphase (SEI) build-up often result in significant safety concerns, high cell resistance, and poor cycle life. The intrinsic high reactivity between lithium metal with conventional lithium ion electrolytes (organic carbonate-based solvents) makes it extremely difficult to overcome these problems. In this project, Wildcat performed focused, fundamental research and development on composite polymer/ceramic electrolytes and protected lithium metal anodes to develop an all solid state lithium metal battery targeting the DOE requirements to enable commercialization. Wildcat successfully leveraged its high throughput battery platform and explored a broad composite electrolyte compositional space. Additionally, Wildcat screened large numbers of inorganic and organic coatings for lithium metal protection using in situ liquid methods and translated the best results to all solid cells. The proposed composite polymer/ceramic electrolyte and a protected lithium metal anode enabled a solid-state lithium metal battery. The ultimate targets from this effort will deliver a safe all solid-state lithium metal pouch cell with over 350 Wh/kg and over 1,000 cycles (C/3) with the cost estimate below $100/kWh. During the course of the project, we demonstrated stable cycling of 10’s of cycles with the composite SSE and our protected lithium. The work has continued after the conclusion of the DOE funding, demonstrating further improvements in catholyte composition and thinner composite solid electrolytes.