SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Disclosed herein are methods and systems that relate to an on-line monitoring of a process/system by controlling rate of oxidation of metal ions at an anode in an anode electrolyte of an electrochemical process and controlling rate of reduction of the metal ions in a catalysis process to achieve steady state.
Additive manufacturing has the potential to revolutionize industrial hardware and unlock efficiency gains through the fabrication of geometries and architectures not possible by conventional processing. Wire Arc Additive manufacturing (WAAM) process is a class of directed energy deposition process enabling higher build rate and allowing custom wire feedstock allowing spatial variation of microstructure. The larger spot size and lower speed creates a larger melt pool, reducing residual stress and often time creating directional/columnar microstructure for Ni-superalloy. The use of flexible platform provides freedom in deposition strategy, which can accommodate complex substrates, including feature addition onto existing structures, non-flat layers, and repair methods. However, the certification of the final component needs to match the strength requirement. Hence, the quality of the component produced is stringently monitored to avoid buildup of residual stress, cracks, porosity and to reduce detrimental segregated phases commonly observed during alloy solidification. Simulation plays a huge role in predicting the melt pool dimension and can be used to optimize the process parameter. Similar development is also required to perform physics-based modeling of microstructural development in WAAM that can predict the microstructural features during solidification and can be used to optimize the process more effectively. To move toward this goal, Raytheon Technologies Research Center together with Siemens worked to create a set of computational tools to control the process parameters, enable on-line measurements and acquisition with feedback to the optimized process parameters, and eventually track material evolution through each step of the additive process. Computational fluid dynamics is used for accurate prediction and calibration of the thermal field during WAAM process. and phase field models for microstructure evolution as a function of processing parameters to establish a connection between additive parameters and the final microstructure. Here we report cellular automata (CA) model development to predict the dendritic microstructure evolution with surface and bulk nuclei for single track and multiple layers. The CA model was developed to account for secondary element addition and predict segregation, local melting, and latent heat release as well as prediction of Euler angles from orientation information and validated against experiments. This framework was utilized to tailor spatially-varying composition in a part by appropriately controlling the microstructure evolution during the additive process. Functionally graded Haynes 282 alloy with high Cr content at the surface was tested for oxidation and mechanical properties. An advanced physics-based reaction-diffusion model predicting the simultaneous creation of chromium oxide and alumina is developed and validated to extend life expectancy of the WAAM manufactured high temperature part. A machine-learning data-driven framework establishing the process-structure relationship from a dataset of real microstructure images and corresponding process history data has been developed and implemented in the NX Siemens design system. The digital twin configuration along with the tool path generation enabled prediction of WAAM component buildup time and the techno-economic analysis provided a favorable option for all 4 cases with 15-40% cost reduction.
Chemical Risk Management is a system or process to control safety and security risks associated with hazardous or toxic chemicals. Chemical Risk Management includes the management of both chemical safety and chemical security. There are five pillars that make up chemical security management10 (Figure 1). Each of the five pillars are key components to the implementation of a chemical security risk management system. In this paper, we will review the "Material Control and Accountability" pillar and how an academic institution can implement this principle using a chemical inventory management system.
We demonstrate the construction of a novel low-noise continuous flow humidity controller and its integration with a commercial variable-temperature atomic force microscope fluid cell, allowing precise control of humidity and temperature at the sample during nanoscale measurements. Based on wet and dry gas mixing, the design allows a high mechanical stability to be achieved by means of an ultrasonic atomiser for the generation of water-saturated gas, improving upon previous bubbler-based architectures. Water content in the flow is measured both at the inflow and outflow of the fluid cell, enabling the monitoring of water condensation and icing, and allowing controlled variation of the sample temperature independently of the humidity. To benchmark the performance of the controller, the results of detailed noise studies and time-based imaging of the formation of ice layers on highly oriented pyrolytic graphite are shown.
Spin-dependent processes involving nonadiabatic transitions between electronic states with different spin multiplicities play important roles in the chemistry of complex systems. The rates of these processes can be predicted based on the molecular properties at the minimum energy crossing point (MECP) between electronic states. We present the development of the MECP search technique within the fragment molecular orbital (FMO) method applicable to large complex systems. The accuracy and scalability of the new method is demonstrated on several models of the metal-sulfur protein rubredoxin. The effect of the model size on the MECP geometry and relative energy is discussed. The fragment energy decomposition and spin density delocalization analyses reveal how different protein residues and solvent molecules contribute to stabilization of the spin states. The developed FMO-MECP method can help to clarify the role of nonadiabatic spin-dependent processes in complex systems and can be used for designing mutations aimed at controlling these processes in metalloproteins, including spin-dependent catalysis and electron transfer.
We report on the formation of Pt nanoparticle monolayers by electrophoretic deposition from nonpolar solvents. First, the growth kinetics of Pt nanoparticles prepared by the reverse micelle technique are described in detail. Second, a model of nanoparticle charging in nonpolar media is discussed and methods to control the nanoparticle charging are proposed. Lastly, essential parameters of the electrophoretic deposition process to control the deposition of nanoparticle monolayers are discussed and mechanisms of their formation are analyzed.
Manufacturing is central to the nation’s prosperity and security. Manufacturing currently represents about 12% of the gross domestic product, provides nearly 13 million jobs, and accounts for about 25% of energy use. The nation’s economy relies heavily on wide-ranging manufacturing sectors - all of which share common challenges including data issues, lack of physics and chemistry-based models across scales, and resource constraints in a global environment. Furthermore, there are many hurdles that must be overcome to move basic science innovations to market. Addressing broad-ranging challenges demands a basic-science strategy that underpins applied research activities. This strategy would accelerate innovation and transform manufacturing. A Basic Research Needs workshop for Transformative Manufacturing was held in March 2020. The focus of the workshop was to identify the basic science research priorities that could accelerate innovation to transform manufacturing in the future. This was the first workshop of its kind to examine how basic energy science can drive manufacturing forward and innovate new ways to manufacture goods. Five Priority Research Directions were identified that address these science challenges: (1) innovative synthetic approaches to enable scalable assembly of matter, (2) computational methods and theoretical models to transform how manufacturing processes are controlled, (3) new characterization tools that can handle the necessary complexity, scales, and processing speeds to meet manufacturing needs, (4) new science to address opportunities relevant to sustainable and energy-efficient manufacturing, and (5) foundational approaches to co-design of materials, process, and products.
This report is based on a Basic Research Needs workshop for Transformative Manufacturing, which was held March 9 - 11, 2020. The focus of the workshop was to identify the basic science research priorities that could accelerate innovation to transform manufacturing in the future. This was the first workshop of its kind to examine how basic energy science can drive manufacturing forward and innovate new ways to manufacture goods. Five Priority Research Directions were identified that address these science challenges: (1) innovative synthetic approaches to enable scalable assembly of matter, (2) computational methods and theoretical models to transform how manufacturing processes are controlled, (3) new characterization tools that can handle the necessary complexity, scales, and processing speeds to meet manufacturing needs, (4) new science to address opportunities relevant to sustainable and energy efficient manufacturing, and (5) foundational approaches to co-design of materials, process, and products.
The present invention relates to vanadium oxide and methods of controlling reaction processes for making such materials (e.g., powders). In particular embodiments, the method includes control of oxygen partial pressure in order to kinetically control the oxidation species of the crystalline vanadium oxide material. Other methods, uses, systems, protocols, and coatings are also described.
The present invention relates to vanadium oxide and methods of controlling reaction processes for making such materials (e.g., powders). In particular embodiments, the method includes control of oxygen partial pressure in order to kinetically control the oxidation species of the crystalline vanadium oxide material. Other methods, uses, systems, protocols, and coatings are also described.
Nuclear Power Plants (NPPs) are a complex system of coupled physics controlled by a network of Programmable Logic Controllers (PLCs). These PLCs communicate process data across the network to coordinate control actions with each other and inform the operators of process variables and control decisions. Networking the PLCs allows more effective process control and provides the operator more information which results in more efficient plant operation. This interconnectivity creates new security issues, as operators have more access to the plant controls, so will bad actors. As plant networks become more digitized and encompass more sophisticated controllers, the network surface exposed to cyber interference grows. Understanding the dynamics of these coupled systems of physics, control logic, and network communications is critical to their protection. The research into the cybersecurity of the Operational Technologies of NPPs is developing and requires a platform that can allow high fidelity physics simulations to interact with digital networks of controllers. This will require three main components: a network simulation environment, a physics simulator, and virtual PLCs (vPLC) that represent typical industry hardware. A platform that incorporates these three components to provide the most accurate representation of actual NPP networks and controllers is developed in this paper.
Control Room modernization is an important part of life extension for the existing light water reactor fleet. None of the 99 currently operating commercial nuclear power plants in the U.S. has completed a full-scale control room modernization to date. A full-scale modernization might, for example, entail replacement of all analog panels with digital workstations. Such modernizations have been undertaken successfully in upgrades in Europe and Asia, but the U.S. has yet to undertake a control room upgrade of this magnitude. Instead, nuclear power plant main control rooms for the existing commercial reactor fleet remain significantly analog, with only limited digital modernizations. Previous research under the U.S. Department of Energy’s Light Water Reactor Sustainability Program has helped establish a systematic process for control room upgrades that support the transition to a hybrid control. While the guidance developed to date helps streamline the process of modernization and reduce costs and uncertainty associated with introducing digital control technologies into an existing control room, these upgrades do not achieve the full potential of newer technologies that might otherwise enhance plant and operator performance. The aim of the control room benefits research presented here is to identify previously overlooked benefits of modernization, identify candidate technologies that may facilitate such benefits, and demonstrate these technologies through human factors research. This report serves as an outline for planned research on the benefits of greater modernization in the main control rooms of nuclear power plants.
Electrorefining is a controlled redox process used to regulate the behavior of ionic species. Through this process, metals can be deposited onto a cathode from an electrolyte solution in a controlled manner. The Mk-IV electrorefiner (Mk-IV ER) at Idaho National Laboratory is an engineering-scale, molten salt-based electrorefining cell that has been used for decades to recover metallic uranium from spent fuel. As a result, highly stable fission product chlorides have accumulated in the electrolyte. This accumulation results in changes to the salt’s properties, such as melting temperature, thermal conductivity, and density, as well as elevated product impurity and fissile materials criticality margin. These factors prompt the need for a salt regeneration process, such as melt-crystallization and species drawdown. This work focuses on providing a conceptual design to regenerate ER salt from used Mk-IV-ER salt in-situ, while minimizing salt waste volumes by concentrating the fission products in a final processed salt heal. We propose using a hot-finger crystallization apparatus design to fractionally crystallize salt in the Mk-IV-ER head space (or baffle space), allowing the collection of solid and liquid fractions. By using a cup-drain design, the used salt will be allowed to slowly solidify on the walls of a stainless-steel cup. The apparatus drain plug will then open to allow the liquid salt phase to drain to a lower cup, effectively separating the liquid phase from the solid phase. Under the hypothesis that the liquid phase salt concentrates the fission products, which is under examination in the accompanying work package, this separation allows the recovered solid salt to be reused while minimizing the high-level salt waste volume of used ER salt.
Control Room modernization is an important part of life extension for the existing light water reactor fleet. None of the 99 currently operating commercial nuclear power plants in the U.S. has completed a full-scale control room modernization to date. A full-scale modernization might, for example, entail replacement of all analog panels with digital workstations. Such modernizations have been undertaken successfully in upgrades in Europe and Asia, but the U.S. has yet to undertake a control room upgrade of this magnitude. Instead, nuclear power plant main control rooms for the existing commercial reactor fleet remain significantly analog, with only limited digital modernizations. Previous research under the U.S. Department of Energy’s Light Water Reactor Sustainability Program has helped establish a systematic process for control room upgrades that support the transition to a hybrid control room. While the guidance developed to date helps streamline the process of modernization and reduce costs and uncertainty associated with introducing digital control technologies into an existing control room, these upgrades do not achieve the full potential of newer technologies that might otherwise enhance plant and operator performance. The aim of the control room benefits research is to identify previously overlooked benefits of modernization, identify candidate technologies that may facilitate such benefits, and demonstrate these technologies through human factors research. This report describes the initial upgrades to the HSSL and outlines the methodology for a pilot test of the HSSL configuration.
In order to improve the pulp quality and to reduce the energy consumption, the fiber length distribution (FLD) is generally employed as one of the important technological indexes in the refining process. Considering that the traditional mean and variance of fiber length are unable to adequately characterize the non-Gaussian distribution properties, this paper proposes a novel geometric analysis based double closed-loop iterative learning control (ILC) method for probability density function (PDF) shaping of output FLD in the refining process. Primarily, a RBF neural network (NN) with Gaussian-type is utilized to approximate the square root PDF in the inner loop, where the RBF basis function parameters (center and width) are tuned between any two adjacent batches by using an ILC law, and the subspace identification method can be applied to establish the state-space model of weight vector. Then, for the sake of accelerating the convergence rate of the closed-loop sysyem, a geometric analysis based ILC method is adopted in the outer loop. Lastly, both simulation and experiments demonstrate the effectiveness and practicability of the proposed approach.
Particles of Cu x Al y in Sn-Cu-Al solders have previously been shown to nucleate the Cu 6 Sn 5 phase during solidification. In this study, the number and size of Cu 6 Sn 5 nucleation sites were controlled through the particle size refinement of Cu x Al y via rapid solidification processing and controlled cooling in a differential scanning calorimeter. Cooling rates spanning eight orders of magnitude were used to refine the average Cu x Al y and Cu 6 Sn 5 particle sizes down to submicron ranges. The average particle sizes, particle size distributions, and morphologies in the microstructures were analyzed as a function of alloy composition and cooling rate. Deep etching of the samples revealed the three-dimensional microstructures and illuminated the epitaxial and morphological relationships between the Cu x Al y and Cu 6 Sn 5 phases. Transitions in the Cu 6 Sn 5 particle morphologies from faceted rods to nonfaceted, equiaxed particles were observed as a function of both cooling rate and composition. Initial solidification cooling rates within the range of 10 3 to 10 4 °C/s were found to be optimal for realizing particle size refinement and maintaining the Cu x Al y /Cu 6 Sn 5 nucleant relationship. In addition, little evidence of the formation or decomposition of the ternary-β phase in the solidified alloys was noted. As a result, solidification pathways omitting the formation of the ternary-β phase agreed well with observed room temperature microstructures.
Mineral–water interfacial reactions are central to chemical processes that control the fate of nutrients and contaminants in natural environments. Mineral surfaces commonly have complex structures and compositions whose impact on interfacial reactivity is poorly understood. Here, in this work, we investigated the effects of surface heterogeneities on Rb + sorption at the quartz (101)–10 mM RbCl solution interface at pH 9.8 using in situ high-resolution X-ray reflectivity. Two surface locales (i.e., Spots A and B) having distinct interfacial structures were chosen: Spot A was characterized by its low defect density (≤20% topmost Si vacancies) and Rb + adsorption occurred predominantly as an inner-sphere complex. In comparison, Spot B had a higher defect density (~50% vacancies) and was covered with poorly crystalline SiO 2 . A substantially larger Rb + uptake (i.e., 7-times higher coverage) was observed on this defective surface where Rb + incorporated in the vacancy sites (confirmed by density functional tight binding-based molecular dynamics simulations) or adsorbed directly on the disordered film. These results provide a direct quantification of how surface heterogeneity influences the geochemical behavior of mineral–water interfaces, in particular highlighting the important role of chemical and structural defects on the sorbate speciation and coverage at silicate mineral surfaces.