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At least 1,099 records · Page 61

Solar PV, Wind Generation, and Load Forecasting Dataset for ERCOT 2018: Performance-Based Energy Resource Feedback, Optimization, and Risk Management (P.E.R.F.O.R.M.)

This report describes the Advanced Research Projects Agency-Energy Performance-Based Energy Resource Feedback, Optimization, and Risk Management (PERFORM) Electric Reliability Council of Texas (ERCOT) dataset consisting of load, solar, and wind deterministic and probabilistic forecasts at three timescales. This dataset consists of 1 year of time-coincident load, wind, and solar actuals and probabilistic forecasts for a region similar to ERCOT. All the data are stored in Hierarchical Data Format 5 (HDF5) files and have been uploaded to an Amazon Web Services repository. The ERCOT data set has 2 years (2017, 2018) of actuals and 1 year (2018) of probabilistic forecasts. These data are provided at various spatial (i.e., site-level, zone-level, and system-level) and temporal scales (i.e., day-ahead, intraday, and intra-hour). Specifically, data are provided for 125 existing wind sites, 22 existing solar sites, 139 proposed wind sites, and 204 proposed solar sites.

14 SOLAR ENERGY↗

Design of Graded Cathode Catalyst Layers with Various Ionomers for Fuel Cell Application

Proton exchange membrane fuel cells (PEMFCs) powered by green hydrogen (H2) have become a promising alternative to conventional hydrocarbon-fueled power generators. Despite technological advancements, further improvements in efficiency, durability, and low-cost production are required for the widespread adoption of PEMFCs. Though numerous approaches to improve PEMFC electrodes have been reported, most strategies utilize a single material set (e.g., one combination of catalyst and ionomer) to improve performance. Alternatively, anisotropic (graded) electrode structures with locally tunable properties may yield superior electrode performance due to improved ionic and gas phase transport. In this work, graded cathode catalyst layers (CCLs) incorporating different ionomers (Nafion D2020, Aquivion D79-25BS, and HOPI) were designed and prepared. Performance screening shows that some of these graded electrode structures have comparable performance to optimized single-ionomer electrode structures (D2020) suggesting some synergistic benefit. Additionally, we show that electrodes with lower equivalent weight (EW) D79 ionomer near the membrane and D2020 ionomer near the gas diffusion media outperformed electrodes with the inverted configuration. Finally, EIS analysis shows some graded ionomer structures (e.g. D79/D2020) have better than expected H+ conductivity, generally leading to better electrode performance. However, further optimization of ionomer content and catalyst ink formulations is needed to improve overall PEMFC performance.

DIRECT ENERGY CONVERSION↗

Intelligent Agents for the Optimization of Atomic Layer Deposition

Atomic layer deposition (ALD) is a highly controllable thin film synthesis approach with applications in computing, energy, and separations. The flexibility of ALD means that it can access a massive chemical catalogue; however, this chemical and process diversity results in significant challenges in determining processing parameters that result in stable and uniform film growth with minimal precursor consumption. In situ measurements of the ALD growth per cycle (GPC) can accelerate process development but it still requires expert intuition and time-consuming trial and error to identify acceptable processing parameters. This procedure is made more difficult by the presence of experimental noise in the GPC values and the complexity of ALD surface chemistries. Here, a need exists for efficient optimization approaches capable of autonomously determining processing conditions resulting in optimal ALD film growth. In this work, we present the development of three optimization strategies and compare their performance in optimizing four simulated ALD processes. Furthermore, the effect of noise in the GPC measurements on optimization convergence is studied.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Delay-resolved spectroscopy in terahertz photonic circuits

Photonic integrated circuits incorporating intersubband transitions are ideal for mid-infrared and terahertz nanophotonics. However, the design of epitaxies has long been inhibited by two factors: the modest predictivity of ab initio theory and the absence of absolute intersubband gain and loss measurements under operating conditions. Existing measurements either yield inaccurate gain profiles or do not accurately assess dependence on frequency, bias, and temperature. Here, we present a delay-resolved absolute-referencing method for accurate gain evaluation without these limitations, addressing a long-standing challenge. By creating a photonic circuit that allows broadband pulses to traverse different lengths of a gain medium, we measure the absolute transmission of intersubband structures. Gain profiles match theoretical predictions at lower temperatures, with gain and dispersion clamping after lasing, and faster-than-expected degradation occurs at higher temperatures. Our approach provides a precise experimental evaluation of temperature-dependent gain performance and gives insight into optimizing temperature performance and frequency comb designs.

Optical spectroscopy↗

Effect of Interlayer Time-Lapse and Workability Retention on Printed Concrete Performance

The rapid advancement of additive manufacturing technologies for concrete construction requires further understanding of material performance and its relationship with print parameters such as interlayer time-lapse and workability retention during the print. Here this study addresses the effects of the time delay between consecutive extruded layers on the mechanical performance of printed concrete using a mix designed by Quikrete. A series of specimens were prepared with printing delays of 10, 15, 30, and 60 min. This work correlates the change in fracture properties, mechanical performance, and workability retention with the interlayer time-lapse between two consecutive concrete layers. Interlayer time-lapse is defined as the time difference in printing of two consequent layers of concrete. It affects individual properties differently based on the loading direction and test types, but it is consistent in terms of interlayer performance. The understanding of the effect of interlayer time-lapse on the fracture properties between two consecutive printed layers fills the knowledge gaps in printed concrete research. Therefore, this study can help researchers perform required optimization and safely estimate the performance of printed concrete.

3D printing↗

Extreme Fast Charging Lithium-Ion Batteries (Final Technical Report)

The objective of this research project is to develop, design, fabricate, and demonstrate lithium ion battery cells that optimize energy density, reduce cost, and demonstrate eXtreme Fast Charging (XFC) capabilities. The XFC capability of the cell will be determined by the final specific energy of the cell after completing 500 6C charge /1C discharge cycles. Over the first 18 months of the project, over 800 cells were produced in groups of 20 cells to determine the optimum configuration of following parameters to optimized XFC performance: (1) Graphite anode material optimization (2) Electrolyte and additive optimization (3) Electrode and cell design optimization. In the final 6 months of the project, over 200 optimized cells were produced that featured optimized parameters from each of the independent studies. The final optimized cells exhibited a final specific energy of 150 Wh/kg, meeting the DOE project goal, but failing to meet the initial specific energy requirement of 180 Wh/kg.

25 ENERGY STORAGE↗

Aeroelastic Simulation of Transonic Truss-Braced Wing Aircraft for Flight Dynamic Stability Analysis

This paper presents aeroelastic simulation of the Mach 0.8 Transonic Truss-Braced Wing (TTBW) aeroelastic model using CFD solver FUN3D for the flight dynamic and control stability analysis. A jig twist optimization is performed to obtain a flight optimized jig twist for the flexible Mach 0.8 TTBW model. The developed aeroelastic model steady-state stability derivatives with respect to the angle of attack, angle of sideslip, and airspeed are calculated with perturbations in the angle of attack, angle of sideslip, and Mach number, respectively. A series of unsteady simulations is conducted for the developed aeroelastic model in pitch oscillation at various reduced frequencies. The dynamic stability derivatives are estimated using a frequency domain estimation method. The control derivatives of the elevator, rudder, and ailerons of the developed aeroelastic model are estimated for control stability analysis.

TTBW↗

Effects of Aeroelasticity on Buffet Onset of Mach 0.8 Transonic Truss-Braced Wing

This paper presents a buffet simulation of the Mach 0.8 Transonic Truss-Braced Wing (TTBW) aeroelastic model using CFD solver FUN3D. A jig twist optimization is performed to obtain a flight optimized jig twist for the flexible Mach 0.8 TTBW model. A series of Delayed Detached Eddy Simulation (DDES) aeroelastic simulations has been conducted at Mach number 0.8 and altitude 40,000 ft using a structural damping of 2% to compare the pitch break prediction and the buffet behavior for the TTBW aeroelastic model. The unsteady pressure begins to grow at angle of attack of 4.0 ◦ , which might indicate the buffet onset, and rises one order of magnitude larger at angle of attack of 4.5 ◦ . In contrast, the buffet onset for the TTBW 1g model appears to be at the angle of attack of about 3.5 ◦ . The delay in the buffet onset of the aeroelastic model is due to the load relief from the aeroelastic effect.

TTBW↗

From Data to Knowledge: A Graph-Based Reliability Approach to Assess System Health

With the goal of maximizing plant reliability and availability, complex systems such as nuclear power plants continuously monitor and record the performance and the health status of many components, assets, and systems. Such data may take the form of online monitoring data, condition reports, and maintenance reports and it carries the potential to provide system engineers with insights into anomalous behaviors or degradation trends as well as the possible causes behind them and to predict their direct consequences. The analysis of such data poses however few challenges. While some of these challenges are technical in nature (i.e., data are often distributed over several physical servers or databases), others are conceptual in nature (i.e., data elements come in different formats, numeric or textual), and measured values have different scales (e.g., vibration spectra and oil temperature). This paper directly tackles these challenges, and it focuses on the integration of all these data elements in order to assist plant system engineers in analyzing component, assets, and systems performances and optimize maintenance activities. This is performed by 1) extracting knowledge from textual data via technical language processing methods, and 2) quantifying system, asset, and component health from numeric condition-based data. We rely on model-based system engineering (MBSE) models of systems and assets to identify their architecture and functional (i.e., cause and effect) relations. Numeric and textual data elements are then associated with an MBSE graph element, based on their nature. This bonding of MBSE models and data elements constitutes a first-of-its-kind knowledge graph of a nuclear power plants system, with data elements being organized in a structured manner that enables system engineers to identify cause-effect trends in data elements and carry out appropriate actions in response.

97 MATHEMATICS AND COMPUTING↗

Near-optimal combination of high performance and insensitivity in a shock compressed high explosive single crystal

Achieving the desired combination of superior detonation performance and insensitivity to shock initiation has been a long-standing goal in high explosive (HE) science and technology. Having previously established the shock insensitivity of 1,1-diamino-2,2-dinitroethene (also known as DADNE or FOX-7) single crystals to 20 GPa (extended to 25 GPa in this work), the FOX-7 detonation response was determined through wave profile measurements in ~250 μm thick single crystals shock compressed to 64 GPa. Quite unexpectedly, FOX-7 demonstrated the classic Chapman–Jouguet (C–J) detonation response—reaction completion in the detonation front (<0.7 ns) at pressures of 44 GPa and higher—not observed in other insensitive high explosives. Here, the experimentally determined C–J pressure (35 GPa), detonation wave velocities and the detonation products equation of state—together with shock insensitivity to 25 GPa—demonstrate that FOX-7 single crystals display a near-optimal combination of high performance and shock insensitivity, not observed in another HE crystal.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Update on HCDstruct - A Tool for Hybrid Wing Body Conceptual Design and Structural Optimization

HCDstruct is a Matlab® based software tool to rapidly build a finite element model for structural optimization of hybrid wing body (HWB) aircraft at the conceptual design level. The tool uses outputs from a Flight Optimization System (FLOPS) performance analysis together with a conceptual outer mold line of the vehicle, e.g. created by Vehicle Sketch Pad (VSP), to generate a set of MSC Nastran® bulk data files. These files can readily be used to perform a structural optimization and weight estimation using Nastran’s® Solution 200 multidisciplinary optimization solver. Initially developed at NASA Langley Research Center to perform increased fidelity conceptual level HWB centerbody structural analyses, HCDstruct has grown into a complete HWB structural sizing and weight estimation tool, including a fully flexible aeroelastic loads analysis. Recent upgrades to the tool include the expansion to a full wing tip-to-wing tip model for asymmetric analyses like engine out conditions and dynamic overswings, as well as a fully actuated trailing edge, featuring up to 15 independently actuated control surfaces and twin tails. Several example applications of the HCDstruct tool are presented.

Gern, Frank H.↗

Blade and Rim Seal Design of a First Stage High Pressure Turbine for a 300 MWe Supercritical CO2 Power Cycle

A first stage high-pressure turbine (HPT) blade is optimized for a 300 MWe supercritical CO2 (sCO2) power cycle using the surrogate-assisted genetic algorithm optimizer in Numeca FINE/Design 3D with objectives of increasing efficiency and decreasing heat load to the blade. The National Institute of Standards and Technology Reference Fluid Thermodynamic and Transport Properties Database (NIST REFPROP) [1] data for supercritical CO2 is formatted into tables of bicubic polynomial coefficients for use in condensable gas simulations in FINE/Turbo. Nearly 3000 unique shapes are evaluated via three-dimensional Reynolds Averaged Navier Stokes simulations, yielding increases in efficiency of up to 0.85 percentage points and decreases in heat load of 14%. A final blade, deemed the advanced blade, is chosen for future experimental analysis. Following this, a squealer tip optimization is performed on both the baseline and advanced blade designs. This optimization resulted in a performance gain of 1.25 points in efficiency and 15% reduction in tip heat load compared to the baseline flat tip design at the same clearance. In tandem, an optimization of the rotor-stator platform rim seal is performed using a parametrized geometry allowing for straight, meandering, and knife seal cavities. This multi-objective optimization focuses on decreasing the cooling mass flow and increasing the heat flux from the rotor and stator disk. The optimization resulted in cooling mass flow decreases of up to 26% while maintaining the average heat flux on the rim seal.

Tuite, Logan↗

The role of under-determined approximations in engineering and science application

There is currently a great deal of interest in using response surfaces in the optimization of aircraft performance. The objective function and/or constraint equations involved in these optimization problems may come from numerous disciplines such as structures, aerodynamics, environmental engineering, etc. In each of these disciplines, the mathematical complexity of the governing equations usually dictates that numerical results be obtained from large computer programs such as a finite element method program. Thus, when performing optimization studies, response surfaces are a convenient way of transferring information from the various disciplines to the optimization algorithm as opposed to bringing all the sundry computer programs together in a massive computer code. Response surfaces offer another advantage in the optimization of aircraft structures. A characteristic of these types of optimization problems is that evaluation of the objective function and response equations (referred to as a functional evaluation) can be very expensive in a computational sense. Because of the computational expense in obtaining functional evaluations, the present study was undertaken to investigate under-determinined approximations. An under-determined approximation is one in which there are fewer training pairs (pieces of information about a function) than there are undetermined parameters (coefficients or weights) associated with the approximation. Both polynomial approximations and neural net approximations were examined. Three main example problems were investigated: (1) a function of one design variable was considered; (2) a function of two design variables was considered; and (3) a 35 bar truss with 4 design variables was considered.

Carpenter, William C.↗

Ion-chain sympathetic cooling and gate dynamics

Sympathetic cooling is a technique often employed to mitigate motional heating in trapped-ion quantum computers. However, choosing system parameters such as number of coolants and cooling duty cycle for optimal gate performance requires evaluating trade-offs between motional errors and other slower errors such as qubit dephasing. The optimal parameters depend on cooling power, heating rate, and ion spacing in a particular system. In this study, we aim to analyze best practices for sympathetic cooling of long chains of trapped ions using analytical and computational methods. We use a case study to show that optimal cooling performance is achieved when coolants are placed at the center of the chain and provide a perturbative upper bound on the cooling limit of a mode given a particular set of cooling parameters. In addition, using computational tools, we analyze the trade-off between the number of coolant ions in a chain and the center-of-mass mode heating rate. We also show that cooling as often as possible when running a circuit is optimal when the qubit coherence time is otherwise long. These results provide a roadmap for how to choose sympathetic cooling parameters to maximize circuit performance in trapped-ion quantum computers using long chains of ions.

Cooling & trapping↗

Quantification of In-flight Physical Changes: Anthropometry and Neutral Body Posture

Currently, NASA does not have sufficient in-flight anthropometric data gathered to assess the impact of physical body shape and size changes on suit sizing. For developing future planetary and reduced gravity suits, NASA needs to quantify the impacts of microgravity on anthropometry, body posture, and neutral body postures (NBP) to ensure optimal crew performance, fit, and comfort. To obtain these impacts, anthropometric data, circumference, length, height, breadth, and depth for body segments (i.e. chest, waist, bicep, thigh, calf) from astronauts for pre, in-, and postflight conditions needs to be collected. Once this data has been collected, a comparison between pre, in-, and postflight anthropometric values will be analyzed, yielding microgravity factors. The NBP will be used to determined body posture (joint angle) changes between subjects throughout the duration of a mission. Data collection, starting with Increments 37/38, is still in progress with the completion of 3 out of 12 subjects. NASA suit engineers and NASA's Extravehicular Activity (EVA) Project Office have identified that suit fit in microgravity could become an issue. It has been noted that crewmembers often need to adjust their suit sizing once they are in orbit. This adjustment could be due to microgravity effects on anthropometry and postural changes, and is necessary to ensure optimal crew performance, fit, and comfort in space. To date, the only data collected to determine the effects of microgravity on physical human changes have been during Skylab, STS-57, and a recent HRP study on seated height changes due to spinal elongation (Spinal Elongation, Master Task List [MTL] #221). The Skylab and the STS-57 studies found that there is a distinct neutral body posture (NBP) based on photographs. The still photographs showed that there is a distinguishable posture with the arms raised and the shoulder abducted; and, in addition, the knees were flexed with noticeable hip flexion and the foot plantar flexed [1,2]. This is the one standard set of body joint angles for a NBP in microgravity. A recent simulated microgravity NBP study [3] has shown an individual variability and inconsistencies in defining NBP. This variation may be influenced by spinal growth, the type of suit fit, and other potential anthropometry factors such as spinal curvature, age, and gender. The variation aspect of this essential data is required for all kinds of space device designs (e.g. suits, habitat, mobility aids, etc.). The method proposed considers the dynamic nature of body movement and will use a measurement technique to continually monitor posture and develop a probability likelihood of the natural posture and how the NBP postures are affected by anthropometry. Additionally, Skylab studies found that crewmembers experienced a stature growth of up to 3%. The data included 3 crewmembers that showed that there is a bi-phasic stature growth once the crew enters into weightlessness. However, the Spinal Elongation study identified that the crewmembers could experience about a 6% growth in seated height and a 3% stature growth, when exposed to microgravity. The results prove that not all anthropometric measurements have the same microgravity percent growth factor. For EVA and suit engineers to properly update the sizing protocol for microgravity, they need additional anthropometric data from space missions. Hence, this study is aimed to gather additional in-flight anthropometric measurements, such as length, depth, breadth, and circumference, to determine the changes to body shape and size due to microgravity effects. It is anticipated that by recording the potential changes to body shape and size, a better suit sizing protocol will be developed for ISS and other space missions. In essence, this study will help NASA quantify the impacts of microgravity on anthropometry to ensure optimal crew performance, fit, and comfort. This study will use simplistic data collection techniques, 3D laser scanning, digital still, and video data, and perform photogrammetric analyses to determine the changes that occur to the body shape, size, and NBP when exposed to a microgravity environment.

Young, K. S.↗

Quantification of ln-Flight Physical Changes: Anthropometry and Neutral Body Posture

Currently, NASA does not have sufficient in-flight anthropometric data to assess the impact of changes in body shape and size. For developing future planetary and reduced-gravity suits, NASA needs to quantify the impacts of microgravity on anthropometry and body posture to ensure optimal crew performance, fit, and comfort. To obtain data on these changes, circumference, length, height, breadth, and depth for body segments (chest, waist, bicep, thigh, calf) from astronauts for preflight, in-flight, and post-flight conditions needs to be collected. Once these data have been collected, pre-flight, in-flight, and post-flight anthropometric values will be compared, yielding microgravity factors. The neutral body posture (NBP) will also be measured, to determine body posture (joint angle) changes between subjects throughout the duration of a mission. Data collection, starting with Increments 37/38, is still in progress but has been completed for 6 out of 9 subjects. NASA suit engineers and NASA's Extravehicular Activity (EVA) Project Office have identified that suit fit in microgravity could become an issue. It has been noted that crewmembers often need to adjust their suit sizing once they are in orbit. This adjustment could be due to microgravity effects on anthropometry and postural changes, and is necessary to ensure optimal crew performance, fit, and comfort in space. To date, the only data collected to determine the effects of microgravity on physical human changes were collected during Skylab 4, the Apollo-Soyuz Test Project (ASTP), Space Shuttle mission STS-57, and a recent HRP study on seated height changes due to spinal elongation (Spinal Elongation, Master Task List [MTL] #221). The Skylab 4, ASTP, and the STS-57 studies found that, according to photographs, a distinct NBP exists. The still photographs showed a distinguishable posture with the arms raised and the shoulders abducted; in addition, the knees are flexed, with noticeable hip flexion, and the foot is plantar flexed [1,2]. This combination is considered to be the standard set of body joint angles for an NBP in microgravity. A recent simulated microgravity NBP study [3] showed individual variability and inconsistencies in defining NBP. This variation may be influenced by spinal growth, and other potential anthropometry factors such as spinal curvature, age, and gender. Data on the variation of this posture data is required for all kinds of space device designs (such as suits, habitat, and mobility aids). The method proposed in this study considers the dynamic nature of body movement and will use a measurement technique to continually monitor posture and develop a probability likelihood of the neutral posture and how the NBP postures are affected by anthropometry. Additionally, Skylab studies found that crewmembers experienced a stature growth of up to 3 percent. The data included 3 crewmembers and showed that a biphasic stature growth occurs once the crewmember enters into weightlessness. However, the HRP Spinal Elongation study showed that crewmembers could experience about a 6 percent growth in seated height and a 3 percent stature growth, when exposed to microgravity. The results of that study prove that not all anthropometric measurements have the same microgravity percent growth factor. For EVA and suit engineers to properly update the sizing protocol for microgravity, they need additional anthropometric data from space missions. Hence, this study is aimed at gathering additional in-flight anthropometric measurements, such as length, depth, breadth, and circumference, to determine the changes to body shape and size caused by microgravity effects. It is anticipated that by recording the potential changes to body shape and size, NASA will develop a better suit sizing protocol for the International Space Station and other space missions. In essence, this study will help NASA quantify the impacts of microgravity on anthropometry to ensure optimal crew performance, fit, and comfort. This study will use standard anthropometry data collection techniques, 3D laser scanning, digital still photography, and video data, and perform photogrammetric analyses to determine the changes that occur to the body shape and size, and to NBP, when the human body is exposed to a microgravity environment.

Young, K. S.↗

A Computational Tool Compatible with NEAMS Code Packages for Optimizing the Shape of Nuclear Reactor Components and of Whole Core Performance

We designed and implemented a shape optimization tool that functions with NEAMS codes, and that nuclear scientists and engineers can employ to optimize the shape of individual components and the whole core under the applicable single- or multi-physics model comprising the employed code(s). The shape-optimization tool enables varying the geometric shape itself as well as its dimensions to yield, potentially, new component designs that are not limited by the designer’s intuition and previous experience. In cases where the optimal-shape object is an individual component, we provide the capability for additional verification that the whole-core performance using the optimized component performs better, under the prescribed optimization criteria, than the initial design. Our shape-optimization tool couples to NEAMS codes via a flexible input- composer interface and enables the user to constrain the shape’s evolution to ensure the component’s manufacturability. Finally, we demonstrate our shape-optimization tool with single- and multi-physics NEAMS codes. This objective is motivated by the recent advances in manufacturing technology that, combined with rising interest in novel reactor concepts, are creating new opportunities for innovation in the design of individual components that affect the performance of the full reactor system. In particular, Additive Manufacturing (AM) enables mass production of highly precise, intricate and complex component shapes that are not feasible with traditional manufacturing techniques. To accomplish this goal we developed and implemented in MOOSE: (1) discrete shape optimization capability based on a state-space search that uses Artificial Intelligence strategies to find the optimal state/shape; (2) smooth shape optimization tool that employs PETSc’s toolkit for advanced optimization (TAO) to optimize node-displacement of the components’ model sidesets; (3) hierarchical core optimization workflow that recognizes the repeating patterns typical in a nuclear reactor and performs the optimization one level at a time with increasing length scale. Each of these tools is equipped with user-specified constraints to avoid optimal shapes that are not manufacturable. The developed shape optimization tool is verified and demonstrated on various nuclear reactor core components and models. The optimization process accounts for tightly coupled physics that govern the behavior of these target reactors, and exercises several NEAMS codes in a coupled multiphysics fashion. The impact of the delivered shape optimization tool will materialize in the optimal design, from the outset, of advanced reactors currently contemplated to regain the US’s leadership in nuclear energy R&D. Novel reactor concepts, e.g. Molten Salt Reactors, and sizes/capacities, e.g. micro- reactors, provide a unique opportunity to optimize performance from the early stages of development, before the investment in components’ production lines, validation experiments, and licensing regimes make future improvements in performance prohibitively expensive and force sub-optimal performance on the affected reactor concept in perpetuity. This benefit will be realized by the delivered shape optimization tool regardless of the applicable manufacturing process whether traditional or AM, thereby broadening the impact of this project on current and future reactor concepts and technologies

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗