Process-Based Climate Model Development Harnessing Machine Learning: II. Model Calibration From Single Column to Global
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Fast, digital signal processing (DSP) has many applications. Typical hardware options for performing DSP are field-programmable gate arrays (FPGAs), application-specific integrated DSP chips, or general purpose personal computer systems. This paper presents a novel DSP platform that has been developed for feedback control on the HBT-EP tokamak device. The system runs all signal processing exclusively on a Graphics Processing Unit (GPU) to achieve real-time performance with latencies below 8 μs. Signals are transferred into and out of the GPU using PCI Express peer-to-peer direct-memory-access transfers without involvement of the central processing unit or host memory. Tests were performed on the feedback control system of the HBT-EP tokamak using forty 16-bit floating point inputs and outputs each and a sampling rate of up to 250 kHz. Signals were digitized by a D-TACQ ACQ196 module, processing done on an NVIDIA GTX 580 GPU programmed in CUDA, and analog output was generated by D-TACQ AO32CPCI modules.
The energy and angle of impact of ions, interspersed with fluxes of neutral radicals, on the surface of wafers during plasma materials processing are critical parameters for the fabrication of microelectronic devices, nanostructure materials and biocompatible materials. This sensitivity extends to nearly all applications of plasmas to materials processing and surface modification. Low temperature plasmas for plasma materials processing have traditionally used continuously excited plasmas. However, pulsed plasma processing is an enabling technology for achieving finer resolution of microelectronics fabrication and for producing unique surface properties in a wide range of applications. This research project is addressing fundamental plasma physics issues in materials processing – the control of pulsed plasmas and the means for optimizing plasma produced reactant fluxes.
Use of corn fractionation techniques in dry grind process increases the number of coproducts, enhances their quality and value, generates feedstock for cellulosic ethanol production and potentially increases profitability of the dry grind process. The aim of this study is to develop process simulation models for eight different wet and dry corn fractionation techniques recovering germ, pericarp fiber and/or endosperm fiber, and evaluate their techno-economic feasibility at the commercial scale. Ethanol yields for plants processing 1113.11 MT corn/day were 37.2 to 40 million gal for wet fractionation and 37.3 to 31.3 million gal for dry fractionation, compared to 40.2 million gal for conventional dry grind process.
Combining separate unit operations into one where the best of each part can be maximized is one of the benefits of process intensification. An example is the combination of lignocellulosic biomass enzymatic hydrolysis with the downstream solid-liquid separation step to produce clarified sugars ready for fermentation or catalytic upgrading. The productivity and endpoint yield of enzymatic hydrolysis both enjoy the benefits of reduced feedback inhibition through the continuous removal of sugars by incorporating separations into the reactor. Likewise, the efficiency of recovering clarified sugars from the enzymatic hydrolysis slurry can be enhanced by operating separations equipment at steady-state conditions simultaneously with the continuously fed hydrolysis process. A key parameter that enables greater processing capacity while also raising the risks of failure is the solids loading or concentration. Higher solids loading allows for smaller reactor vessels and results in clarified sugars of higher concentration; however, required pumping power increases, reactor agitation may become ineffective, and membrane flux suffers. Feedstock material attributes influenced by upstream pretreatment must also be scrutinized more carefully: dilute-acid pretreated and deacetylated-and-disc-refined feedstocks exhibit different characteristics that affect agitation and pumping. The authors invite you to further explore the process science enabling the scale-up of this technology from conceptual work at the bench to pilot-scale industrially-relevant equipment where the challenges and solutions of integration and process optimization are expounded upon.
The recent revolution in shale gas has presented opportunities for distributed manufacturing of key commodity chemicals, such as methanol, from methane. However, the conventional methane-to-methanol process is energy intensive which negatively affects the profitability and sustainability. Here an intensified process configuration that is both economically attractive and environmentally sustainable. This flowsheet is systematically discovered using the building block-based representation and optimization methodology. The new process configuration utilizes membrane-assisted reactive separations and can have as much as 190% higher total annual profit compared to a conventional configuration. Additionally, it has 57% less CO 2 -equivalent greenhouse gas emission. Such drastic improvement highlights the advantages of building block-based computer-aided process intensification method.
Coal and coal byproducts produced annually contain enough rare earth elements (REEs) to meet current U.S. demand. Here, the REEs exist in the form of minerals, ion-exchanged elements associated with clays and chemically bonded elements within the organic coal matrix. Researchers at three universities have collaborated to evaluate the effectiveness of existing physical and chemical concentration processes for the recovery of the REEs. The efforts have found that physical separation processes can increase the total REE content in the thickener underflow material collected from a Central Appalachian coal cleaning facility from around 300 ppm to values greater than 17,500 ppm on an ash basis. Leaching followed by solvent extraction was found to be the most effective to recover the REEs from coarse middlings materials collected from multiple coal basins as indicated by recovery values exceeding 80%. Based on material characterization data and process evaluations conducted for several potential feed coal sources, economic recovery of the REEs will require byproduct production of both clean coal and REE concentrate using a process flowsheet that is unique for each source.
Abstract The industrial Air Separations Unit (ASU) is a complicated and tightly operated process. The use of dynamic process analytics is also a key element of safe and economic operation of these processes, with increasing focus on predictive analytics to take preemptive actions. With the availability of real‐time data from hundreds of sensors, the data analysis process should also consider the topology of the data, as seen in sensor networks. In this paper, a novel tool is presented that considers the complex connectivity patterns in the sensor network and uses local adaptive disturbance estimations to predict global network‐scale trends. The paper introduces the emerging field of Graph Signal Processing (GSP) and presents a rigorous derivation of the tool starting from the extraction of the sensor‐network (in a graph theoretical sense) from the data. This network, which is in the form of a matrix, is then used to derive a Kalman‐filter type of state‐space model driven by input disturbances. Multiple disturbance models (e.g., step, ramp, periodic) are included to allow the model to have different kinds of disturbance propagation. Each graph node (representing the sensors used) dynamically adapts to the most recent detected disturbance individually. These estimated disturbances are propagated to the global network using the graph. Modifications to ensure stability are also discussed. The fidelity of the tool is tested on certain downtime events and the paper concludes by discussing the advantages of the method and planned future improvements.
The relative dispersion of cloud and fog droplets has significant impacts on aerosol indirect effects, radiative transfer, and microphysical processes. However, previous studies have been mostly concerned with clouds, with limited studies on fog, particularly those that examine the combined influences of all key physical processes and their roles during fog evolution. As such, this study aims to conduct a comprehensive investigation by examining the relationships between relative dispersion and other microphysical variables, as well as the underlying microphysical and dynamic processes, based on field fog campaigns in polluted and clean conditions. In polluted fog, droplet concentrations are higher, leading to smaller droplets and increased dispersion. The correlation between dispersion and droplet volume-mean radius is positive in the polluted fog, but shifts to negative in clean fog. Here, we attribute the difference to various microphysical processes like aerosol activation, condensation, collision-coalescence, and entrainment-mixing. In polluted fog, high aerosol concentrations, low supersaturations, and strong turbulence (entrainment-mixing) provide suitable conditions for the simultaneous occurrence of droplet condensation and aerosol activation, resulting in a positive correlation between dispersion and volume-mean radius, especially during the fog formation stage. In contrast, during the mature stage in clean fog, condensation is dominant with weak aerosol activation leading to a negative correlation between relative dispersion and volume-mean radius. The collision-coalescence process is more active in the mature stage, increasing radii and leading to the negative correlation between dispersion and volume-mean radius. This result sheds new light on understanding the relative dispersion and mechanisms in fog under different aerosol backgrounds.
Abstract The Rapid Bioconversion with Integrated recycling Technology (RaBIT) process uses enzyme and yeast recycling to improve cellulosic ethanol production economics. The previous versions of the RaBIT process exhibited decreased xylose consumption using cell recycle for a variety of different micro-organisms. Process changes were tested in an attempt to eliminate the xylose consumption decrease. Three different RaBIT process changes were evaluated in this work including (1) shortening the fermentation time, (2) fed-batch hydrolysate addition, and (3) selective cell recycling using a settling method. Shorting the RaBIT fermentation process to 11 h and introducing fed-batch hydrolysate addition eliminated any xylose consumption decrease over ten fermentation cycles; otherwise, decreased xylose consumption was apparent by the third cell recycle event. However, partial removal of yeast cells during recycle was not economical when compared to recycling all yeast cells.
In this paper, the thermomechanical process and hot rolling process were carried out to study the microstructure evolution and mechanical property of low-alloy steel used for armor layer of flexible pipes by analyzing continuous cooling transformation curve, microstructure morphology, grain characteristics, and strength. The experimental results indicate that deformation process promotes phase transformation process of both ferrite and bainite and induces the formation of fine grain. The density of low-angle grain boundary rises with increasing cooling rate. The dislocation concentration in grain becomes larger with the extended cooling rate. The microstructure of hot-rolled specimen consists of polygonal ferrite and granular bainite, which is consistent with one of the deformed specimens with similar cooling rate in dilatometer. The microstructure evolution provides effective data fundament for hot rolling process.
Machining is a severe plastic deformation process, wherein the workpiece material is subjected to high deformation rates and temperatures. During metal machining, the dynamic recrystallization mechanism causes grain refinement into the sub-micron range. In this study, we investigate the microstructure evolution of oxygen-free high conductivity copper (OFHC Cu) subject to a machining process where the cutting speed and rake angle are controlled to manipulate the process strain, strain rate, and temperatures. Microstructures of the deformed chips are quantified using orientation imaging microscopy and novel statistical descriptors that capture the morphology and local lattice misorientations generated during the several mechanistic stages of the dynamic recrystallization process. Mechanical properties of the resulting chips are quantified using spherical nanoindentation protocols. A multiple output Gaussian process regression model is used to simultaneously model the structure-property evolution, which differs from more common approaches that establish such relationships sequentially. This modeling strategy is particularly attractive since it can flexibly provide both structure and property uncertainty estimates. In addition, the statistical modeling framework allows for the inclusion of multi-fidelity data. The statistical metrics utilized serve as efficient microstructure descriptors, which retain the physics of the observed structures without having to introduce ad hoc microstructure feature definitions.
We report that fabrication of parts with high mechanical properties heavily depend on the quality of powder deployed in the fabrication process. Copper powder in three different powder types were spheroidized using radio-frequency inductively coupled plasma (ICP) spheroidization process (TekSphero-15 system). The characterized powders include virgin powder as purchased from the powder manufacturer, powder used in electron beam powder bed fusion (EB-PBF) process, and reconditioned powder, which was used powder that underwent an oxygen-reduction treatment. The goal of spheroidizing these powder types was to evaluate the change in powder morphology, the possibility of enhancing the powder properties back to their as-received conditions, and assess oxygen reduction of the powder lots given their initial oxygen contents. Also, to investigate the impact of re-spheroidization on powder properties, the second round of spheroidization was performed on the already used-spheroidized powder. The impact of powder type on powder sphericity and particle size distribution was evaluated using the image analysis of scanning electron microscope (SEM) micrographs and laser diffraction, respectively. The spheroidized powder showed higher sphericity and more uniform particle size distribution overall. Depending on the powder collection bin, second round of spheroidization affected the powder sphericity differently. The possibility of deploying the plasma spheroidization process as an alternative oxygen-reduction technique was also investigated through tracking the powders’ oxygen content using inert gas fusion method before and after the spheroidization. The plasma spheroidized powder showed less oxygen content than the hydrogen-treated powder. The second round of spheroidization caused no change in oxygen content. The correlation between oxygen-reduction and created cracks was discussed and compared between plasma spheroidization and hydrogen-treatment. The plasma spheroidization process created a powder with higher sphericity, uniform particle size, and less oxygen content.
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