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At least 1,801 records · Page 100

Winter wheat: A model for the simulation of growth and yield in winter wheat

The basic ideas and constructs for a general physical/physiological process level winter wheat simulation model are documented. It is a materials balance model which calculates daily increments of photosynthate production and respiratory losses in the crop canopy. The partitioning of the resulting dry matter to the active growing tissues in the plant each day, transpiration and the uptake of nitrogen from the soil profile are simulated. It incorporates the RHIZOS model which simulates, in two dimensions, the movement of water, roots, and soluble nutrients through the soil profile. It records the time of initiation of each of the plant organs. These phenological events are calculated from temperature functions with delays resulting from physiological stress. Stress is defined mathematically as an imbalance in the metabolite supply; demand ratio. Physiological stress is also the basis for the calculation of rates of tiller and floret abortion. Thus, tillering and head differentiation are modeled as the resulants of the two processes, morphogenesis and abortion, which may be occurring simulaneously.

Baker, D. N.↗

Isotherm Modeling and Techno-Economic Analysis of Contactor Technologies for New Tetraamine-Appended MOF for NGCC Applications

Recently, a family of tetraamine-functionalized metal-organic frameworks (MOF) has been reported as promising sorbent materials for capturing CO2 from flue gas conditions relevant to natural gas combined cycle (NGCC) applications. The main advantages of these materials are their two-step cooperative CO2 adsorption, which gives rise to unusual two step-shaped CO2 adsorption profiles and their high thermal stability. This work presents the modelling of the two-transition isotherm of the tetraamine-appended MOF, N,N'-bis(3-aminopropyl)-1,4-diaminobutane (3-4-3)-appended Mg2(dobpdc), and the techno-economic analysis (TEA) of carbon capture processes utilizing this sorbent. Due to the unusual isotherm shapes of the experimental CO2 adsorption data for tetraamine-appended Mg2(dobpdc) and the strong nonlinearity of CO2 loading with respect to temperature and pressure, we tested two different models which use logistic functions for representing the different isotherm behaviors in the different pressure ranges. The first model uses the quadratic isotherm model in the low-pressure region, the Langmuir isotherm model in the middle pressure range, and the dual site Langmuir isotherm model in the high-pressure range. To model the transition between regions we used the arctangent functions independent of temperature and the thermal effect was accounted by using the Clausius-Clapeyron relation]. The second model is an extension of the weighted dual-site Langmuir isotherm model presented by Hughes et al.. In this extended model, the dual-site Langmuir isotherm is employed in the three transition regions, using temperature-dependent logistic functions to activate or deactivate the isotherm model in the low, middle, and high-pressure ranges. Both models fit the experimental data quite well with root mean squared errors (RMSE’s) of 0.41 and 0.17 for model 1 and model 2, respectively. Since model 2 resulted in a lower RMSE, it was leveraged for the development of the gas/solid contactor models used by the TEA. Specifically, two different contactor models, an axial-flow fixed bed and moving bed contactor, were developed as part of this work. These models are dynamic, pressure-driven, and consist of mass, energy, and momentum conservation equations. A kinetic model was also developed by performing parameter estimation using experimental fixed bed breakthrough data. These models are then used to simulate CO2 capture processes from the flue gas generated from a ~600 gross MW NGCC power plant. A cost model was developed which considers the capital cost of the reactors and the significant operating costs such as steam and electricity. Using NETL’s Framework for the Optimization and Quantification of Uncertainty of Uncertainty and Surrogates tool (FOQUS), which has the capability of linking models built using numerous modelling platforms with derivative-free optimization solvers, a techno-economic optimization of the carbon capture processes was performed which minimizes the cost of capture.

Caballero, Daison↗

FULL RANGE TUNE SCAN STUDIES USING GRAPHICS PROCESSING UNITS WITH CUDA IN EIC BEAM-BEAM SIMULATIONS

The hadron beam in the Electron-Ion Collider (EIC) suffers high order betatron and synchro-betatron resonances. In this paper, we present a weak-strong full range (0.0 ~ 0.5) fractional tune scan with a step size as small as 0.001. Multiple Graphics Processing Units (GPUs) are used to speed up the simulation. A code parallelized with MPI and CUDA is implemented. The good tune region from weak-strong scan is further checked by the self-consistent strong-strong simulation. This study provides beam dynamics guidance in choosing proper working points for the future EIC.

43 PARTICLE ACCELERATORS↗

Computer-aided analysis and design of the shape rolling process for producing turbine engine airfoils

Mild steel (AISI 1018) was selected as model cold rolling material and Ti-6A1-4V and Inconel 718 were selected as typical hot rolling and cold rolling alloys, respectively. The flow stress and workability of these alloys were characterized and friction factor at the roll/workpiece interface was determined at their respective working conditions by conducting ring tests. Computer-aided mathematical models for predicting metal flow and stresses, and for simulating the shape rolling process were developed. These models utilized the upper bound and the slab methods of analysis, and were capable of predicting the lateral spread, roll separating force, roll torque, and local stresses, strains and strain rates. This computer-aided design system was also capable of simulating the actual rolling process, and thereby designing the roll pass schedule in rolling of an airfoil or a similar shape.

Lahoti, G. D.↗

Pseudo-dynamic Aspen Plus{sup R} Model of the Defense Waste Processing Facility - 18475

The Defense Waste Processing Facility (DWPF) at the Savannah River Site converts legacy high-level waste from the Cold War into borosilicate glass for permanent disposal in a geological repository. The waste sludge is chemically adjusted by the addition of acid, mixed with frit, and concentrated in the DWPF Chemical Process Cell (CPC) to ensure that the final glass has the desired properties. The resulting mixture is fed into the melter where the waste is melted and poured into stainless steel storage canisters. We present an Aspen Plus{sup R} model of the DWPF CPC, which is being developed to aid chemical processing decisions pertaining to the current flowsheet and to aid decisions regarding optimizing future processing. Given a waste feed composition with acid and frit additions, the model will predict the sludge and off-gas compositions throughout the processing, as well as the final melter feed composition. This allows different processing scenarios to be investigated easily, reducing the reliance on experimental testing, and hence saving time and money. The model has multiple potential applications, including calculating the acid and frit additions required to give acceptable glass properties, off-gas permitting, tracking mercury steam-stripped from the waste in the off-gas system, tracking flammable gases in the offgas system, investigating the effect of reducing air purges in the condensers, and general process optimization. The waste is processed in the CPC in batches, requiring dynamic simulation to track the time-dependent operations. Accurate modeling of the processing also requires calculations of phase and electrolyte chemical equilibria and parallel rate-dependent reactions. Due to existing technical limitations with dynamic simulation of the complex chemical system, we have adopted a pseudo-dynamic approach in which time intervals are treated as consecutive steady-state operations in Aspen Plus{sup R}. Thus, the model consists of ∼100 replicas of the processing vessel and its off-gas system, with the sludge output by one replica (representing one time interval) becoming the feed to the next (representing the next time interval). By examining the results from these replicas in sequence, one can see the time evolution of the model. This general approach can be used wherever simultaneous calculation of phase and electrolyte chemical equilibria in a dynamically evolving system is needed. In addition to describing the general structure and chemistry of the model, we present results from tests of the model against experimental data. These data are from laboratory-scale process simulations of the CPC with a nonradioactive waste sludge simulant. These tests include the model's predictions of the offgas composition, the sludge pH, and the final sludge composition. We will also discuss planned future developments of the model. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Reduction of CO 2 Emissions Through Lightweight Body Panels (Project Final Report)

Lightweight construction is an integral part of Volkswagen’s overall strategy of reducing CO 2 emissions. Due to its low cost, steel is the most commonly used material for automotive exterior body panels today. Unfortunately, steel has a high density, resulting in a relatively low specific strength. Glass fiber based sheet molding compounds (SMC) provide high properties in combination with lower density. The high specific strength of SMC offers an enormous lightweight potential. To unlock the full potential of SMC materials in combination with cutting edge manufacturing processes, Volkswagen Group of America worked together with IACMI (Institute for Advanced Composites Manufacturing Innovation) and the academic partners: University of Tennessee Knoxville, Purdue University and Michigan State University; as well as the industry partners: Ashland, IDI, Owens Corning and Continental Structural Plastics. Leveraging the expertise of all project partners, reaching over the entire supply chain the project demonstrated the potential of these materials. This report will highlight the major steps in the development process on the way to technology readiness for SMC using the example of the Volkswagen Atlas Liftgate. Over the 36-month period of the project, the work focused on three R&D areas: material development, design and simulation, and development of the manufacturing process. Material selection included alternative fibers and resin systems, and accounted for material availability, properties, and cost-efficiency. The work undertaken in the field of design and simulation has pushed the envelope of short fiber reinforced thermoset molding compound process simulation. Design iterations were virtually tested, while the final design was used to validate the simulation software against physical parts. Manufacturing development used cutting-edge technology, while experts along the supply chain were working together to ensure the best possible results. In the final stage of the project, liftgates were molded, trimmed, bonded, painted and assembled before exhaustive testing. The result is an e-coat (electrophoretic dip coating) capable Class-A SMC liftgate, which is ready for high-volume production, and can be used as a technology demonstrator. The prototypes manufactured in the scope of this work have exhibited a mass reduction for the Volkswagen Atlas liftgate of up to 35% compared to the series production steel version, without a degradation of the functionalities.

36 MATERIALS SCIENCE↗

Metal additive manufacturing simulation across length, time, and computing scales

Metal additive manufacturing (AM) offers a unique opportunity for production of advanced materials and complex geometries. However, variability in microstructure and properties challenges conventional approaches to design, process optimization, qualification, and materials selection. Modeling and simulation can improve understanding of AM processing and materials, but also poses major challenges for existing computational methods. Simultaneously, modern scientific computing hardware has become increasingly complex, most notably with the adoption of hybrid architectures such as Graphical Processing Units (GPUs). If appropriately utilized, emerging computational capabilities provide an opportunity to reveal new insight into AM processing and the resulting material structure and properties. In this review we describe the computational AM landscape, identify critical gaps, and highlight opportunities to impact the development and application of AM. First, the requirements and challenges of representative AM problem statements will be defined. Here, these problems range from scientific studies to industrial applications and are designed to capture the breadth of challenges facing the AM community. Next, the current state of AM modeling and simulation is evaluated, broken down by enabling hardware and software, process simulation, microstructure simulation, and property simulation. Each section describes the diversity of simulation approaches and associated trade-offs in physical fidelity and computational expense. Each area is then assessed based on their suitability and readiness for current and developing computational architectures. Lastly, the greatest opportunities for future research and application are highlighted, including gaps in modeling capabilities, opportunities for near-term application, and key scientific challenges.

additive manufacturing↗

Open‐Source Anaerobic Digestion Modeling Platform, Anaerobic Digestion Model No. 1 Fast (ADM1F)

An open‐source modeling platform, called Anaerobic Digestion Model No. 1 Fast (ADM1F), is introduced to achieve fast and numerically stable simulations of anaerobic digestion processes. ADM1F is compatible with an iPython interface to facilitate model configuration, simulation, data analysis, and visualization. Faster simulations and more stable results are accomplished by implementing an advanced open‐source library of numerical methods called Portable Extensive Toolkit for Scientific Computation (PETSc) to solve the ADM1 system of equations. Leveraging PETSc, ADM1F can consistently complete a steady‐state simulation under 0.2 s, over 99% faster than a benchmark ADM1 model implemented with MATLAB while achieving agreement of model outputs within 1% of those obtained with the benchmark model. For dynamic simulations, however, ADM1F has a computational speed advantage only when the influent characteristics update more frequently than every 4 h. The ability of ADM1F to be useful as a tool to study anaerobic digestion systems is demonstrated through two example implementations of ADM1F: (1) a two‐phase co‐digestion scenario evaluating the impact of the organic loading rate and the substrate composition on reactor performance and stability, and (2) a conventional digester scenario assessing the effectiveness of recovery strategies after disruptions that led to instability. These examples demonstrate how the high simulation speed and the convenience of the iPython interface allow ADM1F to complete complex analyses within minutes, much faster than computational strategies currently reported in the literature.

anaerobic co-digestion↗

Computer-aided Veress needle guidance using endoscopic optical coherence tomography and convolutional neural networks

During laparoscopic surgery, the Veress needle is commonly used in pneumoperitoneum establishment. Precise placement of the Veress needle is still a challenge for the surgeon. In this study, a computer-aided endoscopic optical coherence tomography (OCT) system was developed to effectively and safely guide Veress needle insertion. This endoscopic system was tested by imaging subcutaneous fat, muscle, abdominal space, and the small intestine from swine samples to simulate the surgical process, including the situation with small intestine injury. Each tissue layer was visualized in OCT images with unique features and subsequently used to develop a system for automatic localization of the Veress needle tip by identifying tissue layers (or spaces) and estimating the needle-to-tissue distance. We used convolutional neural networks (CNNs) in automatic tissue classification and distance estimation. In conclusion, the average testing accuracy in tissue classification was 98.53 ± 0.39%, and the average testing relative error in distance estimation reached 4.42 ± 0.56% (36.09 ± 4.92 μm).

59 BASIC BIOLOGICAL SCIENCES↗

A sparse Gaussian sigmoid basis function approximation of hyperspectral data for detection of solids

We define a new characterization of emissivity and reflectance curves for compositional exploitation of hyperspectral data. Here, our method decomposes each spectrum into a sparse set of Gaussian sigmoid components using penalized regression. Detection is based on the combination of Gaussian sigmoid components unique to a target material. Focusing on the presence of spectral upslopes and downslopes rather than spectral correlations makes detection more robust to both target variation and spectral variability from atmosphere and background encountered during the collection process. We present simulation studies that demonstrate the potential to reduce false positive rates without compromising sensitivity. Characterization of long–wave infrared (LWIR) experimental data validates our method using minerals of different particle sizes, measurement angles, and collection conditions.

97 MATHEMATICS AND COMPUTING↗

Strain Field Around Individual Dislocations Controls Failure

Understanding material failure on a fundamental level is a key aspect in the design of robust structural materials, especially for metals and alloys capable to undergo plastic deformation. In the last decade, significant progress is made in quantifying the stresses associated with failure in both experiments and simulations. Nonetheless, the processes occurring on the most essential level of individual dislocations that govern semi-brittle and ductile fracture are still experimentally not accessible, limiting the failure prediction capabilities. Therefore, in the present work, a one-of-a-kind nanoscale fracture experiment is conducted on a single crystalline Cr bending beam in situ in the transmission electron microscope and for the first time quantify the transient strains around individual dislocations, as well as of the whole dislocation network during crack opening. The results reveal the importance of both pre-existing and newly emitted dislocations for crack-tip shielding via their intrinsic strain field and provide guidelines to design more damage tolerant materials.

36 MATERIALS SCIENCE↗

Process-driven roadmap for depositing super duplex stainless steel via wire Arc additive manufacturing

Here, this study systematically investigates the effects of shielding gas, bead spacing, weld mode, and travel speed on the phase balance, porosity, and hardness of wire arc additively manufactured (WAAM) super duplex stainless steel (ER2594). Robotic WAAM was employed to fabricate multilayer walls under systematically varied process conditions, followed by phase transformation simulations, X-ray computed tomography (XCT), electron backscatter diffraction (EBSD), and microhardness evaluation. Thermodynamic simulations predicted rapid cooling of AM process can suppress the potential formation of deleterious precipitates which was later validated via cross-sectional microstructure analyses of printed samples. XCT revealed porosity levels below 0.2% for all deposits, with reduced travel speed significantly lowering defect volume. Microstructural analyses revealed the evolution of various austenite precipitates, including grain boundary austenite (GBA), Widmanstätten austenite (WA), and intergranular austenite (IGA), sequentially upon cooling of the ferrite phase. Among all process parameters, weld transfer mode exhibited the strongest influence on phase balance; pulsed mode promoted higher ferrite retention (~ 36%) compared to RapidX mode. No consistent relationship between stabilized phase fraction and captured microhardness was observed. This work provides critical insights for optimizing WAAM parameters to control phase balance and mechanical performance, which is essential for producing high-integrity super duplex stainless-steel components for nuclear and marine applications.

Grain orientation↗

Advances in Multimodal Characterization of Structural Materials

The myriad detectors and instruments now available for materials characterization provide researchers with an ever-growing suite of tools to probe material behavior. Progress in the development of instrumentation and workflows that enable the collection, and leverage the potential, of various data modalities have provided novel insights into material behavior. Using data across multiple length scales, or performing complementary analyses of in situ and ex situ data, can help reveal a more complete picture of dynamic processes or material structure. However, the accurate combination, or fusion, of these disparate data modalities presents new challenges. Differences in resolution, as well as the varying length scales at which physical phenomena are exploited to generate these data, necessitate novel approaches to accurately interpret and combine these data. Furthermore, the papers within this special topic focus on the collection and fusion of multimodal data to better understand structural materials. From new frameworks and workflows for data segmentation and analysis, process monitoring, enhancing simulations, or interrogating mechanical response, these papers reveal the potential benefits of utilizing multimodal data.

36 MATERIALS SCIENCE↗

Shock-induced amorphization in silicon carbide

While silicon carbide (SiC) has been predicted to undergo pressure-induced amorphization, the microstructural evidence of such a drastic phase change is absent as its brittleness usually prevents its successful recovery from high-pressure experiments. In this paper we report on the observation of amorphous SiC recovered from laser-ablation-driven shock compression with a peak stress of approximately 50 GPa. Transmission electron microscopy reveals that the amorphous regions are extremely localized, forming bands as narrow as a few nanometers. In addition to these amorphous bands, planar stacking faults are observed. Large-scale non-equilibrium molecular dynamic simulations elucidate the process and suggest that the planar stacking faults serve as the precursors to amorphization. Finally, our results suggest that the amorphous phase produced is a high-density form, which enhances its thermodynamical stability under the high pressures combined with the shear stresses generated by the uniaxial strain state in shock compression.

36 MATERIALS SCIENCE↗

ICAT: A numerical scheme to minimize numerical diffusion in advection-dispersion modeling and its application in identifying flow channeling

The advection-dispersion equation for scalar transport is essential for the numerical modeling of many fluid dynamics problems. However, solutions from numerical schemes always suffer from numerical diffusion and/or oscillation. In this study, we develop an Intra-Cell Advection Tracking (ICAT) scheme to minimize numerical diffusion and preserve monotonicity for advection-dispersion modeling. The key idea is to introduce “queues” in each discretized cell, and using a sequential transport rule and a flow distribution mechanism to track the scalar transport in these queues temporally and spatially. The capability and limitations of ICAT are first investigated through three test cases. Compared with the results obtained from other numerical schemes, the results from ICAT show substantially reduced numerical diffusion and agree better with analytical solutions. We also employ ICAT to simulate the transport process of a conservative tracer in a fracture with a highly heterogeneous aperture distribution. We report discrete flow channels in the fracture are better discerned by ICAT than by other numerical schemes, indicating the suitability of ICAT for modeling tracer transport in channelized flow fields.

15 GEOTHERMAL ENERGY↗

SPARTA: A flux adjustment methodology to interpret complex experiments

For the accurate determination of reactivity from a detector count rate, correction of spatial effects is of prime importance. This spatial correction is often provided using simulation methodologies, but this may introduce a bias if the result of the experiment is also used as input data for the simulation. Here, this work presents a flux adjustment methodology able to infer experimental reactivity and correction of spatial effects without the need for a simulation. It can process the signal from a complex experiment such as a heat balance measurement in the TREAT reactor, where control rods are continuously adjusted to maintain a constant power. In the present work, this methodology successfully computed the reactivity and the local spatial variation of the flux of a generated signal. It also proved to be robust against noise and errors on kinetic parameters and provides a credible interpretation of a heat balance experiment in TREAT. Efficiency of flux adjustment methods for complex experiment enable a better experiment interpretation less reliant on nuclear data evaluation.

73 - NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Microstructural dependence of defect formation in iron-oxide thin films

In this report passivating iron-oxide films are grown atop iron films simulating the corrosion process in a nuclear reactor environment. Two oxide films grown via physical vapor deposition at 600 °C and room temperature exhibited dense-epitactic and columnar-polycrystalline, microstructures respectively. A third oxide film grown in open air at 600 °C exhibited an eqiuaxed, porous morphology. Cubic maghemite and magnetite phases in each oxide film were identified via grazing incidence X-ray diffraction. Positron annihilation spectroscopy was used to characterize point defects and measure their depth and size distributions in each oxide layer and showed a range of average positron lifetimes from 0.23 ns in the high temperature, vapor deposited film, 0.35 ns in the room temperature-grown film, and 0.31 ns in the thermally grown oxide. These data indicate that the film morphology, which varies greatly in these films, leads to very different defect content. Finally, four-dimensional scanning transmission electron microscopy was used to measure the internal stress of each film and was correlated to the strain state presented in the X-ray diffraction spectra. The defect formation in each film is reasoned through using a thin film growth model.

36 MATERIALS SCIENCE↗

Ignition delay times of NH 3 /DME blends at high pressure and low DME fraction: RCM experiments and simulations

Here, autoignition delay times of ammonia/dimethyl ether (NH 3 /DME) mixtures were measured in a rapid compression machine with DME fractions of 0, 2 and 5 and 100% in the fuel. The measurements were performed at equivalence ratios $\varphi$= 0.5, 1.0 and 2.0 and pressures in the range 10–70 bar; depending on the fuel composition, the temperatures after compression varied from 610 K to 1180 K. Admixture of DME is seen to have a dramatic effect on the ignition delay time, effectively shifting the curves of ignition delay vs. temperature to lower temperatures, up to ~250 K compared to pure ammonia. Two-stage ignition is observed at $\varphi$= 1.0 and 2.0 with 2% and 5% DME in the fuel, despite the pressure being higher than that at which pure DME shows two-stage ignition. At $\varphi$= 0.5, a reproducible pre-ignition pressure rise is observed for both DME fractions, which is not observed in the pure fuel components. A novel NH 3 /DME mechanism was developed, including modifications in the NH 3 subset and addition of the NH 2 + CH 3 OCH 3 reaction, with rate coefficients calculated from ab initio theory. Simulations faithfully reproduce the observed pre- ignition pressure rise. While the mechanism also exhibits two-stage ignition for NH 3 /DME mixtures, both qualitative and quantitative improvement is recommended. The overall ignition delay times for ammonia/DME mixtures are predicted well, generally being within 50% of the experimental values, although reduced performance is observed for pure ammonia at $\varphi$= 2.0. Simulating the ignition process, we observe that the DME is oxidized much more rapidly than ammonia. Analysis of the mechanism indicates that this ‘early DME oxidation’ generates reactive species that initiate the oxidation of ammonia, which in turn begins heat release that raises the temperature and accelerates the oxidation process towards ignition. The reaction path analysis shows that the low-temperature chain-branching reactions of DME are important in the early oxidation of the fuel, while the sensitivity analysis indicates that several reactions in the oxidation of DME, including cross reactions between DME and NH 3 species presented here, are critical to ignition, even at fractions of 2% DME in the fuel.

10 SYNTHETIC FUELS↗

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