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A method is proposed for modeling the lost-wax casting of tool electrodes by means of fusible BrA9ZhZL copper-based alloy. The functionality of the casting system is analyzed. The heating and cooling of a ceramic mold is taken into account in visualizing the temperature fields. Sections where shrinkage pores may form in the casting are identified.
Atmosphere-only experiments are widely used to investigate climate feedbacks simulated in more computationally expensive fully coupled global climate model simulations. We confirm that this remains a valid approach by comparing the radiative feedbacks and forcing between coupled and atmosphere-only simulations for the latest models taking part in the 6th phase of the Coupled Model Intercomparison Project (CMIP6). For global-mean cloud feedbacks, we find a better than previously known correspondence between these experiments, which applies even to the response of individual cloud properties (amount, altitude, and optical depth) and holds even when considering atmosphere-only simulations of only 1 yr duration. For regional cloud feedbacks, the correspondence between the two experiments is generally present at every geographic location except for the tropical Pacific but takes longer experiments to reveal. For the lapse rate and surface albedo feedbacks, the correspondence between the two experiments is weaker due to the non-uniform warming pattern and loss of sea ice in the coupled experiment. For the across-model relationship between 4xCO 2 effective radiative forcing and feedback, we find a different behavior across experiments in CMIP6 than in CMIP5, casting doubt on the physical significance of previous results that highlighted an anti-correlation between the two quantities. Overall, these results confirm the utility of atmosphere-only experiments particularly to study cloud feedbacks, which are the dominant source of inter-model spread in climate sensitivity.
Wind power forecasting is an important tool in power system operations to address variability and uncertainty. Accurately doing so is important to reducing the occurrence and length of curtailment, enhancing market efficiency, and improving the operational reliability of the bulk power system. This research quantifies the value of wind power forecasting improvements in the IEEE 118-bus test system as modified to emulate the generation mixes of Midcontinent, California, and New England independent system operator balancing authority areas. To measure the economic value, a commercially available production cost modeling tool was used to simulate the multi-timescale unit commitment (UC) and economic dispatch process for calculating the cost savings and curtailment reductions. To measure the reliability improvements, an in-house tool, FESTIV, was used to calculate the system's area control error and the North American Electric Reliability Corporation Control Performance Standard 2. The approach allowed scientific reproducibility of results and cross-validation of the tools. A total of 270 scenarios were evaluated to accommodate the variation of three factors: generation mix, wind penetration level, and wind fore-casting improvements. The modified IEEE 118-bus systems utilized 1 year of data at multiple timescales, including the day-ahead UC, 4-hour-ahead UC, and 5-min real-time dispatch. The value of improved wind power forecasting was found to be strongly tied to the conventional generation mix, existence of energy storage devices, and the penetration level of wind energy. The simulation results demonstrate that wind power forecasting brings clear benefits to power system operations.
In summer monsoon regions the monthly mean precipitation regions coincide approximately well with regions of westerlies at low-levels. An included chart shows a 15-year (1979-1993) mean August 850 hPa zonal wind from NCEP/NCAR reanalysis dataset and Xie-Arkin precipitation. It shows a region of westerlies covering most of Northern Indian Ocean and extending to northwestern Pacific. This region coincides well with the region with precipitation greater than 6 mm/day. Obviously the coincidence is not exact; the region of larges; zonal wind in the Arabian Sea is in a region of relatively low precipitation and is far from the region of maximum precipitation in Bay of Bengal. Also, in a zonally averaged sense between 40E and 140E, the latitude of maximum precipitation is slightly higher than that of the maximum zonal wind. Low-level westerlies are also found in regions west of Central America and in western Africa north of the equator. These regions are also closely associated with precipitation centers. Across equator from these westerlies regions there are regions of strong easterlies. Also, on their poleward side the westerly regions are flanked by weaker easterly regions. In February, similar observation can be found in the Australian monsoon area and in South America monsoon region; again the regions of westerlies coincide well with regions of maximum precipitation. As in the northern hemisphere, the maximum precipitation is found to the cast of the maximum zonal wind. The two maxima lie almost at the same latitude with that of the westerlies slightly closer to the equator. In the non-monsoon seasons the low- level westerlies can also be found in the tropical precipitation regions, the longitudinal range of the westerlies is undiminished and the speed of the westerlies is not much weaker than that found in February. The interpretation of these observational facts is the goal of this investigation. The approach taken is numerical simulation with the Goddard Earth Observation Systems atmospheric general circulation model, and its aqua-planet version, combined with theoretical arguments.
The local microstructure and distribution of thermally induced residual strains in ferrite matrix grains around an individual spherical graphite nodule in ductile cast iron (DCI) were measured using a synchrotron X-ray micro-diffraction technique. It is found that the matrix grains are deformed, containing dislocations and dislocation boundaries. Each of the residual strain components in the matrix grains exhibits a complex pattern along the circumferential direction of the nodule. Along the radial direction of the nodule, strain gradients from the interface to the grain interior are seen for some strain components, but only in some matrix grains. The observed residual strain patterns have been analysed by finite element modelling, and a comparison between the simulation and experiments is given. The present study of local residual stress by both experimental characterization and simulation provide much needed information for understanding the mechanical properties of DCI, and represent an important contribution for the microstructural design of new DCI materials.
Model-based prognostics approaches employ domain knowledge about a system, its components, and how they fail through the use of physics-based models. Component wear is driven by several different degradation phenomena, each resulting in their own damage progression path, overlapping to contribute to the overall degradation of the component. We develop a model-based prognostics methodology using particle filters, in which the problem of characterizing multiple damage progression paths is cast as a joint state-parameter estimation problem. The estimate is represented as a probability distribution, allowing the prediction of end of life and remaining useful life within a probabilistic framework that supports uncertainty management. We also develop a novel variance control mechanism that maintains an uncertainty bound around the hidden parameters to limit the amount of estimation uncertainty and, consequently, reduce prediction uncertainty. We construct a detailed physics-based model of a centrifugal pump, to which we apply our model-based prognostics algorithms. We illustrate the operation of the prognostic solution with a number of simulation-based experiments and demonstrate the performance of the chosen approach when multiple damage mechanisms are active
The Nuclear Regulatory Commission (NRC) has considered revision of 10 CFR 50.46C rule to account for the effects of burn-up rate in future analysis of reactor accident scenarios so that safety margins may evolve with the operation and reloading of the reactor as dynamic limits. In order to find these limiting conditions, both cladding oxidation and maximum temperature must be cast as functions of fuel exposure. It is computationally intensive to run a plant model through a long duration operational transient to the time of fuel reload, and this must be repeated for each reload until the time of the accident scenario. Moreover, fuel reload patterns may differ in many ways so that calculations with many different core configurations must be considered. To perform such new analyses in a reasonable amount of computational time with good accuracy, Idaho National Laboratory (INL) has developed new multi-physics tools by combining existing codes and adding new capabilities. The Parallel Highly Innovative Simulation INL Code System (PHISICS) toolkit for neutronic and reactor physics is coupled with the Reactor Excursion and Leak Analysis Program (RELAP5-3D) for the Loss of Coolant Accident (LOCA) analysis and RAVEN for the Probabilistic Risk Assessment (PRA) and margin characterization analysis. Expansion of code capability was also necessary. For RELAP5-3D to process a single sequence of cores in a continuous run required modification of RELAP5-3D to restart a sequence of input decks, each with a slightly modified neutronics model or thermal-hydraulic flow region and culminating in an accident scenario. A new multi-deck input processing capability was developed and verified for this analysis. In conclusion, the combined RAVEN/PHISICS/RELAP5-3D tool is used to analyze a typical Pressurized Water Reactor (PWR).
The CAST GPS 4000 simulator can create scenarios using external trajectories. The following information must be provided: time from a given epoch (a constant sampling rate must be used); position, velocity and acceleration in Earth Centered Earth Fixed (ECEF) coordinates; elements of the matrix that transforms from the body-axis coordinate system to the ECEF frame; and the angular velocity of the body-axis system relative to ECEF coordinates. The initial latitude, longitude, altitude, and UTC time must also be provided during the scenario setup. The simulator recomputes the positions and velocities using the given accelerations and a constant jerk model. The results are the internal "truth file".
Magnetohydrodynamics (MHD) provides an approximate description of a great variety of processes in space physics. Accurate numerical solutions of the MHD equations are still a challenge, but in the past decade a number of robust methods have appeared. Once these techniques made the direct solution of MHD equations feasible, a number of global three-dimensional models were designed and applied to many space physics objects. The range of these objects is truly astonishing, including active galactic nuclei, the heliosphere, the solar corona, and the solar wind interaction with planets, satellites, and comets. Outside the realm of space physics, MHD theory has been applied to such diverse problems as laboratory plasmas and electromagnetic casting of liquid metals. In this paper we present a broad spectrum of models of different phenomena in space science developed in the recent years at the University of Michigan. Although the physical systems addressed by these models are different, they all use the MHD equations as a unifying basis.
Additive manufacturing has demonstrated the ability to fabricate complex geometries and components not possible with conventional casting and machining. In many cases, industry has demonstrated the ability to fabricate complex geometries with improved efficiency and performance. However, qualification and certification of processes is challenging, leaving companies to focus on certification of material though design allowable based approaches. This significantly reduces the business case for additive manufacturing. Therefore, real time monitoring of the melt pool can be used to detect the development of flaws, such as porosity or un-sintered powder and aid in the certification process. Characteristics of the melt pool in the Direct Laser Sintering (DLS) process is also of great interest to modelers who are developing simulation models needed to improve and perfect the DLS process. Such models could provide a means to rapidly develop the optimum processing parameters for new alloy powders and optimize processing parameters for specific part geometries. Stratonics’ ThermaViz system will be integrated with the Renishaw DLS system in order to demonstrate its ability to measure melt pool size, shape and temperature. These results will be compared with data from an existing IR camera to determine the best approach for the determination of these critical parameters.
Autonomous Identification of Battery Life Models (AI-Batt) AI-Batt is a MATLAB code base for developing lifetime models for batteries from accelerated aging data. The code base provides many functions for processing, visualizing, and modeling battery aging data, making the data processing, exploration, and modeling workflow substantially faster. These tools are tailored for working with battery aging data sets, which usually consist of many separate time-series for each cell, with many test conditions and possible replicates at each condition, which makes it difficult to simply process or visualize the data set. Complex modeling tasks, such as cross-validation, sensitivity analysis, and uncertainty quantification have been implemented to enable thorough statistical investigation of model predictions. Additionally, several machine-learning algorithms are implemented to autonomously identify suitable models via symbolic regression. Data processing functions automatically cast data from the struct data type, which is commonly used to store experimental data, but is not an acceptable input for most algorithms, to the table data type, which can be easily used as input to any optimization algorithm. Also, the data can be separated into time-invariant and time-variant data tables, which is helpful for exploring the data set as well as developing separate models for time-variant and time-invariant aging mechanisms. For example, in aging tests with constant temperature, temperature is a time-invariant experimental condition. Visualization tools enable plotting of data, model fits, and model simulations possible with single-line function calls, empowering data exploration of complex data sets with both time-varying and time-invariant trends. Plots can be automatically generated for the whole data set, or separated by data group (groups of test replicates) or individual data series. Data points or data series can be automatically colored by the value of a variable with a variety of color maps, and model predictions can also be colored by the value of a fit statistic. Comparisons between data sets and the predictions/simulations of different models on the same data set can be easily plotted as well. Distributions of parameter values from bootstrap resampling can be plotted to visualize the reliability of parameter estimation, or determine any correlations between parameters. Modeling tools handle the complex task of creating and parsing symbolic equations for modeling battery lifetime. Equations are parsed to grab relevant data variables, parameter values, or specified sub-models for input into optimization, evaluation, or simulation functions. Models can be optimized locally (one set of parameters for each data series), bi-level (some parameters shared across the data set), or globally (single set of parameters for all data). Functions implementing symbolic regression algorithms help users to discover effective model equations, even in poorly sampled, high-dimensional data.
Within the area of systems health management, the task of prognostics centers on predicting when components will fail. Model-based prognostics exploits domain knowledge of the system, its components, and how they fail by casting the underlying physical phenomena in a physics-based model that is derived from first principles. Uncertainty cannot be avoided in prediction, therefore, algorithms are employed that help in managing these uncertainties. The particle filtering algorithm has become a popular choice for model-based prognostics due to its wide applicability, ease of implementation, and support for uncertainty management. We develop a general model-based prognostics methodology within a robust probabilistic framework using particle filters. As a case study, we consider a pneumatic valve from the Space Shuttle cryogenic refueling system. We develop a detailed physics-based model of the pneumatic valve, and perform comprehensive simulation experiments to illustrate our prognostics approach and evaluate its effectiveness and robustness. The approach is demonstrated using historical pneumatic valve data from the refueling system.
This project was awarded for an initial period of three years, followed by a no-cost extension for one year and a funded one-year renewal. During the first four years, the project focused on investigating the role of dislocation reactions and dislocation correlation in dislocation patterning in FCC metals. During the fifth year, the scope of research was expanded to investigate the effects of composition inhomogeneity on the mesoscale plastic response of Body-Centered Cubic (BCC) alloys. In addition to its impact on metal hardening during deformation, dislocation patterning provides the microstructure information required to understand phenomena like fracture and recrystallization in metals. The Continuum Dislocation Dynamics (CDD) framework was the methodology used during the first four years, followed by the use of Discrete Dislocation Dynamics (DDD) during the fifth year. CDD is a density-based formalism of dislocation dynamics in which the plastic deformation of crystals is predicted together with the mesoscale dislocation patterns by tracking the space-time evolution of dislocations as driven by the applied stress, short-range and long-range interactions of dislocations, and cross slip. CDD is a crystal mechanics approach in which the plastic constitutive part is replaced with the equations of dislocation dynamics, which is driven by the internal stress via a mobility laws, while the evolution of the density gives the eigenstrain required to update the internal stress itself. The governing equations are thus those of crystal mechanics cast as an eigenstrain problem and those of dislocation transport and reactions. Our investigations during the first four years were driven by the hypothesis that that dislocation patterning is triggered by spatiotemporal dislocation density and internal stress fluctuations, and that such fluctuations influence the collective dislocation dynamic through their effects on the short-range reaction rates and the collective dislocation mobility. This hypothesis was tested by modeling the influence of the dislocation reactions and dislocation correlations on collective dislocation dynamics. The main research components during the first four years were: 1) Reformulation of the CDD framework to integrate the dislocation correlations and dislocation reactions. 2) Simulation of the dislocation correlations and quantifying their contribution to the long-range stress of complex dislocation systems. 3) Computational implementation of the updated CDD model for FCC single crystals and development of an efficient CDD code. 4) Investigation of dislocation patterning in FCC crystals based on the updated CDD model. Some key findings from these investigations were: 1) The patterning of dislocations is initiated by cross slip and internal stress fluctuations, and the refinement of the pattern results from junction formation. 2) Patterning is more prominent under high stress. 3) The correlation stress was found to be a significant part of the mean field stress in continuum representations of dislocation dynamics. During the last year of the project, we have established a method for performing dislocation dynamics in inhomogeneous alloys and demonstrated the impact of composition inhomogeneity on the characteristics of initial yielding and dislocation character in BCC alloys. We also tested this method using an irradiated ferritic alloy in which the composition and dislocation loops effects are both present. In doing so, we have considered two aspects of the role of inhomogeneity, the creation of internal coherency stress due to the dependence of the lattice parameter on the local composition, and the dependence of the dislocation mobility on the local composition. These two aspects resulted in an unexpected behavior of the dislocation system, and, in turn, the yielding behavior of BCC alloys. Key findings include: 1) The composition inhomogeneity in BCC alloys alters the well-known role of screw dislocations by forcing a level of waviness on the average dislocation character, thus destroying the screw character dominance in the yielding observed in pure or homogeneous BCC metals. 2) In the case of irradiated alloys, while composition inhomogeneity by itself and dislocation loops by themselves result in some hardening, the superposition of the two mechanisms does not result in the sum of the two contributions via any known rule. The latter result contradicts the classical works related hardening via multiple mechanisms, which state that various hardening mechanisms can be added linearly or using some Pythagorean additive rule. We were able to rationalize this unexpected result by a closer loop at the origin of the hardening mechanisms themselves, which both involved long-range elastic interactions with dislocations. We reached the conclusion that the hardening resulting from the total stress associated with these two mechanisms (current work) differs from the sum of the effects of the individual stress fields (classical literature). We have also found a major flaw in the classical theory of spinodal hardening. The latter theory never considered the impact of composition undulation on the solute hardening. We have built a new general theory accounting for the effect of solute friction together with the composition undulations on the dislocation configuration at Critical Resolved Shear Stress (CRSS), which is yielding a new definition of the spinodal hardening and new different results. This work is the first to recognize the lack of the role of solute in spinodal hardening theory of alloys.
Several model/instrument concepts employing electroless metallic skin were considered for improvement of surface condition, accuracy, and cost of contoured-geometry convective heat transfer models. A plated semi-infinite slab approach was chosen for development and evaluation in a hypersonic wind tunnel. The plated slab model consists of an epoxy casting containing fine constantan wires accurately placed at specified surface locations. An electroless alloy was deposited on the plastic surface that provides a hard, uniformly thick, seamless skin. The chosen alloy forms a high-output thermocouple junction with each exposed constantan wire, providing means of determining heat transfer during tunnel testing of the model. A selective electroless plating procedure was used to deposit scaled heatshield tiles on the lower surface of a 0.0175-scale shuttle orbiter model. Twenty-five percent of the tiles were randomly selected and plated to a height of 0.001-inch. The purpose was to assess the heating effects of surface roughness simulating misalignment of tiles that may occur during manufacture of the spacecraft.
Critical infrastructures such as cyber-physical energy systems (CPS-E) integrate information flow and physical operations that are vulnerable to natural and targeted failures. Safe, secure, and reliable operation and control of CPS-E is critical to ensure societal well-being and economic prosperity. Automated control is key for real-time operations and may be mathematically cast as a sequential decision-making problem under uncertainty. Emergence of data-driven techniques for decision making under uncertainty, such as reinforcement learning (RL), have led to promising advances for addressing sequential decision-making problems for risk-based robust CPS-E control. However, existing research challenges include understanding the applicability of RL methods across diverse CPS-E applications, addressing the effect of risk preferences across multiple RL methods, and development of open-source domain-aware simulation environments for RL experimentation within a CPS-E context. This article systematically analyzes the applicability of four types of RL methods (model-free, model-based, hybrid model-free and model-based, and hierarchical) for risk-based robust CPS-E control. Problem features and solution stability for the RL methods are also discussed. We demonstrate and compare the performance of multiple RL methods under different risk specifications (risk-averse, risk-neutral, and risk-seeking) through the development and application of an open-source simulation environment. Motivating numerical simulation examples include representative single-zone and multizone building control use cases. Finally, six key insights for future research and broader adoption of RL methods are identified, with specific emphasis on problem features, algorithmic explainability, and solution stability.
The main thrust of the work conducted is in the modeling of spectral responses of discontinuous conifer forest canopies, considered as collections of conical forms that are illuminated at an angle and cast shadows on contracting background. The three first-year objectives are: (1) modification of the variance-driven model to incorporate overlapping of shadows and crowns; (2) collection and analysis of photographic data to calibrate tree-spacing functions; and (3) collection of field data to determine height, spacing, and shape of conifers in open and closed stands in the Goosenest (California) test area. Modification of the invertible model uses a linear approximation to correct for the reduction in shadow and canopy area that occurs when shadows fall on crowns or tree crowns intersect. Comparison of the results of the approximation with a series of Monte Carlo simulations shows that the mean area covered by crowns or shadows is approximated quite accurately, but the variance calculated departs significantly from simulated values. The analysis of tree spacing patterns using air photos showed that spacing tended to be somewhat regular at a scale approximately equal to the average distance between trees, but at larger distance scales counts of trees in cells could be approximated acceptably by a Poisson (random) function.
I. Novikau, I. Y. Dodin, E. A. Startsev, I. Joseph, Quantum algorithms for simulating dissipative linear and nonlinear dynamics of plasmas. Invited talk at the 66th Annual Meeting of the APS Division of Plasma Physics, Atlanta, Georgia. Novikau I., Dodin I.Y., Startsev E.A., Encoding of linear kinetic plasma problems in quantum circuits via data compression, Journal of Plasma Physics. 2024;90(4):805900401, doi:10.1017/S0022377824000795. We propose an algorithm for encoding linear kinetic plasma problems in quantum circuits. The focus is on modelling electrostatic linear waves in a one-dimensional Maxwellian electron plasma. The waves are described by the linearized Vlasov–Ampère system with a spatially localized external current that drives plasma oscillations. This system is formulated as a boundary-value problem and cast in the form of a linear vector equation to be solved by using the quantum signal processing algorithm. The latter requires encoding of a matrix in a quantum circuit as a sub-block of a unitary matrix. We propose how to encode in a circuit in a compressed form and discuss how the resulting circuit scales with the problem size and the desired precision.
Over the past several years Pacific Northwest National Laboratory (PNNL) has been actively involved in supporting the U.S. Department of Energy National Nuclear Security Administration Office of Material Management and Minimization (formerly Global Threat Reduction Initiative). The U.S. High- Power Research Reactor (USHPRR) project is developing alternatives to existing highly enriched uranium alloy fuel to reduce the proliferation threat. One option for a high-density metal fuel is uranium alloyed with 10 wt% molybdenum (U-10Mo). Forming the U-10Mo fuel plates/foils via rolling is an effective technique and is actively being pursued as part of the baseline manufacturing process. The processing of these fuel plates requires systematic investigation/understanding of the pre- and post-rolling microstructure, end-state mechanical properties, residual stresses, and defects, their effect on the mill during processing, and eventually, their in-reactor performance. In the work documented herein, studies were conducted to determine the effect of cold and hot rolling the as-cast and homogenized U-10Mo on its microstructure and hardness. The samples were homogenized at 900°C for 48 h, then later annealed for several durations and temperatures to investigate the effect on the material’s microstructure and hardness. The rolling of the as-cast plate, both hot and cold, was observed to form a molybdenum-rich and -lean banded structure. The cold rolling was ineffective, and in some cases exacerbated the as-cast defects. The grains elongated along the rolling direction and formed a pancake shape, while the carbides fractured perpendicularly to the rolling direction and left porosity between fractured particles of UC. The subsequent annealing of these samples at sub-eutectoid temperatures led to rapid precipitation of the ' lamellar phase, mainly in the molybdenum-lean regions. Annealing the samples above the eutectoid temperature did not refine the grain size or the banded microstructure. However, annealing the samples led to quick recovery in hardness as evidenced by a drop in Vickers hardness of 20%. Hot rolling was performed at 650 and 800°C. The hot-rolling mill loads (load separation force) were approximately 40 to 50% less than the cold-rolling for the same reduction and thickness. It was observed that hot rolling the samples with 50% or more reduction in thickness were responsible for dynamic recrystallization in the hot-rolled samples and led to grain refinement. Unlike the cold-rolled samples, the hot-rolled samples did not fracture the carbides and appeared to heal the casting defects. The recovery phenomenon was similar to the cold-rolled samples above the eutectoid temperatures, but owing to the refined grain size, the precipitation of the lamellar phase was far more rapid in these samples and the hardness increased more rapidly than in the cold rolled sample when heated below the eutectoid temperature. The data generated from these rolling efforts has been used to make the process modeling efforts more robust and applicable to all USHPRR partner rolling mills. The flow stress for cold rolling the samples was determined to be between 170-190 ksi, with frictional forces between 0.2 and 0.4 for the PNNL mill. The measured roll separation forces and those simulated using finite element methods for hot and cold rolling for the PNNL rolling mill were in good agreement.