THE PRECALC PROJECT: DEVELOPMENT OF A DYNAMIC MODEL FOR PLUTONIUM PROCESSING
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Here, we report that two-stage dynamic control improves bioprocess robustness as a result of the dynamic deregulation of central metabolism. Dynamic control is implemented during stationary phase using combinations of CRISPR interference and controlled proteolysis to reduce levels of central metabolic enzymes. Reducing the levels of key enzymes alters metabolite pools resulting in deregulation of the metabolic network. Deregulated networks are less sensitive to environmental conditions improving process robustness. Process robustness in turn leads to predictable scalability, minimizing the need for traditional process optimization. We validate process robustness and scalability of strains and bioprocesses synthesizing the important industrial chemicals alanine, citramalate and xylitol. Predictive high throughput approaches that translate to larger scales are critical for metabolic engineering programs to truly take advantage of the rapidly increasing throughput and decreasing costs of synthetic biology.
Current collecting systems moving in the ionosphere will induce electromagnetic wave radiation. The commonly used static analysis is incapable of studying the situation when such systems undergo transient processes. A dynamic analysis has been developed, and the radiation excitation processes are studied. This dynamic analysis is applied to study the temporal wave radiation from the activation of current collecting systems in space. The global scale electrodynamic interactions between a space-station-like structure and the ionospheric plasma are studied. The temporal evolution and spatial propagation of the electric wave field after the activation are described. The wave excitations by tethered systems are also studied. The dependencies of the temporal Alfven wave and lower hybrid wave radiation on the activation time and the space system structure are discussed. It is shown that the characteristics of wave radiation are determined by the matching of two sets of characteristic frequencies, and a rapid change in the current collection can give rise to substantial transient radiation interference. The limitations of the static and linear analysis are examined, and the condition under which the static assumption is valid is obtained.
As part of the homogeneous actinides recycling strategy, the EURO-GANEX process is one of the most promising options to achieve the goal of minor actinides recovery. Improvements made to EURO-GANEX system have resulted in the emergence of the so-called New EURO-GANEX process, where the composition of the solvent has been modified by replacing TODGA and DMDOHEMA with cis-mTDDGA in the organic phase and SO3-Ph-BTP with PyTri-Diol in the aqueous phase in order to resolve important issues. The objective of this work is twofold: evaluate the gamma radiolytic resistance of the new EURO-GANEX process by dynamic irradiation conditions simulating the three main steps of the process, and validate the design of CIEMAT Náyade, CEA Marcel and INL irradiation loop devices since each of them mimics different aspects of the real process. Náyade and the INL loops could irradiate the organic and aqueous phases together, whereas in the CEA loop, the irradiated solvent is recycled continuously inside a platform with several stages of mixer-settlers containing aqueous flows simulating the three main steps of the process. The extraction performances and changes in the composition of the solvent have been analyzed during the irradiation experiment by different techniques: gamma spectrometry and ICP-MS/OES for cations or radioactive tracer extraction, and HPLC-MS to identify and quantify the degradation compounds. Despite some differences between the three-irradiation facilities, this inter-institutional study shows that these three comparative tools provide similar trends in the radiolytic stability of a liquid-liquid extraction system. Favourable extraction results for the different steps are obtained according to the static irradiation studies found in literature. However, the degradation of cis-mTDDGA is appreciable leading to degradation compounds, some of which form precipitates and produce important changes in viscosity, important aspects that must be addressed prior to the successful industrial application of the new EURO-GANEX process.
Using 20 OMEGA laser beams at the Laboratory for Laser Energetics, University of Rochester, to irradiate a flat plastic target in a hollow ring configuration, we created supersonic cylindrical stable plasma jets with self-generated megagauss magnetic fields extending out to >4 mm. These well-collimated magnetized jets possess a number of distinct and novel properties that will allow us to study the dynamics, physical processes, and scaling properties of astrophysical jets with a dynamic range exceeding those of previous laboratory settings. The dimensionless parameters of these laboratory jets fall in the same regime as those of young stellar object jets. These jets will also provide new versatile laser-based platforms to study magnetized shocks, shear flows, and other plasma processes under controllable conditions.
Using 20 OMEGA laser beams at the Laboratory for Laser Energetics, University of Rochester, to irradiate a flat plastic target in a hollow ring configuration, we created supersonic cylindrical stable plasma jets with self-generated megagauss magnetic fields extending out to >4 mm. These well-collimated magnetized jets possess a number of distinct and novel properties that will allow us to study the dynamics, physical processes, and scaling properties of astrophysical jets with a dynamic range exceeding those of previous laboratory settings. The dimensionless parameters of these laboratory jets fall in the same regime as those of young stellar object jets. As a result, these jets will also provide new versatile laser-based platforms to study magnetized shocks, shear flows, and other plasma processes under controllable conditions.
We present a model that explains why galaxies form stars on a timescale significantly longer than the timescales of processes governing the evolution of interstellar gas. We show that gas evolves from a non-star-forming to a star-forming state on a relatively short timescale, and thus the rate of this evolution does not limit the star formation rate (SFR). Instead, the SFR is limited because only a small fraction of star-forming gas is converted into stars before star-forming regions are dispersed by feedback and dynamical processes. Thus, gas cycles into and out of a star-forming state multiple times, which results in a long timescale on which galaxies convert gas into stars. Our model does not rely on the assumption of equilibrium and can be used to interpret trends of depletion times with the properties of observed galaxies and the parameters of star formation and feedback recipes in simulations. In particular, the model explains how feedback self-regulates the SFR in simulations and makes it insensitive to the local star formation efficiency. We illustrate our model using the results of an isolated L {sub *}-sized galaxy simulation that reproduces the observed Kennicutt–Schmidt relation for both molecular and atomic gas. Interestingly, the relation for molecular gas is almost linear on kiloparsec scales, although a nonlinear relation is adopted in simulation cells. We discuss how a linear relation emerges from non-self-similar scaling of the gas density PDF with the average gas surface density.
The ability of recurrent neural networks (RNN) to model nonlinear dynamics of high dimensional process data has enabled data-driven RNN-based fault detection algorithms. Previous studies have focused on detecting faults by identifying the discrepancies in data distribution between the faulty and normal data, as reflected in prediction errors generated by RNN models. However, in industrial processes, variations in data distribution can also result from changes in normal control setpoints and compensatory control adjustments in response to disturbances, making it hard to differentiate between normal and faulty conditions. This paper proposes a fault detection method utilizing a long short-term memory (LSTM) encoder–decoder structure with regularized hidden dynamics and reversible instance normalization (RevIN) to compactly represent high-dimensional measurements for effective monitoring. During training, the hidden states of the model are regularized to form a low-dimensional latent space representation of the original multivariate time series data. As a result, the prediction errors of the latent states can be used to monitor the abnormal dynamic variations, while the reconstruction errors of the measured variables are used to monitor the abnormal static variations. Furthermore, the proposed indices can reflect operating conditions, even when the distribution of test data changes, which helps distinguish faults from normal adjustments and disturbances that controllers can settle. Here, data from numerical simulation and the Tennessee Eastman process are used to illustrate the effectiveness of the proposed fault detection method.
Methods for estimating accelerator performance for dynamic hardware behaviors are disclosed. Computer program code to be executed on a first processing unit is received, and an execution of the computer code on the first processing unit is monitored to determine a plurality of performance characteristics. A plurality of dynamic hardware behaviors is determined by applying a clustering algorithm to the performance characteristics, and an equivalent accelerator portion of computer code to be executed on a second processing unit is generated by translating a set of instructions in a first portion of computer code corresponding to a first one of the plurality of dynamic hardware behaviors to an equivalent set of instructions to be executed on the second processing unit. An estimated measure of performance for executing the equivalent accelerator portion on the second processing unit is determined for the first one of the plurality of dynamic hardware behaviors.
In high pressure fuel injectors, needle opening and closing transients cause complex off-design fluid dynamics behaviors that profoundly impact the spray and mixture formation processes. These dynamics are completely different from what is known to occur in steady state conditions. In this study, diesel spray transients have been investigated in single-hole and 3-hole nozzles, encompassing internal and external nozzle flow and including needle motion, performing highly resolved (2.5 μm) computational fluid dynamics (CFD) simulations. We focused on end-of-injection (EOI) and start-of-injection (SOI) processes, in order to provide insights in to the physics. The liquid fuel, vapor and gas species are modeled with a single-fluid multiphase mixture approach, with diffuse interface, and with large eddy simulations (LES) of the turbulence. Occurrence of phase change due to cavitation is accounted for, and the spray dispersion is described with a turbulent dispersion model. Detailed needle motion data and orifice internal surface are available from xray synchrotron source measurements carried out at Argonne National Laboratory, and shared through the Engine Combustion Network (ECN) community. Simulations are compared against x-ray phase contrast imaging and radiography of the internal and near-exit flow, in addition to optical microscopy data of the near-exit sprays. Simulation results are found to agree well with available experimental data, and are able to realistically capture local and global features. The simulations allow to gain insight into the physics of gas ingestion and dribbles at EOI, for different hole diameters, operating conditions and number of holes. At SOI, timing of liquid appearance out of the injector and spray tip penetration are adequately predicted, by using the EOI flow field as in-nozzle initialization, and by prescribing the measured tip needle displacement with an informed effective valve opening point inferred from the x-ray observations. Lastly, the variation of spreading angle over time is also discussed in detail for the multi-hole case, including hole-to-hole variations. Due to real geometry features and asymmetric needle motion with eccentric components, it is found that the three holes exhibit swirling flows of increasing intensity as the lift decreases, causing the near cone angle to open and spread, in a quasi-hollow cone structure. These features are not observed in axial single-hole injectors because of their relative simplicity and intrinsic symmetry.
Methane production and emission from riverbed sediments constitute a significant yet underexplored component of the river methane budget. Despite their importance, a mechanistic and quantitative understanding of these processes under dynamic flow conditions remains elusive, particularly at the basin scale. In this study, we investigate the multiscale (site-to-basin) mechanisms governing methane emissions from riverbeds, focusing on the interplay between biogeochemical processes and hydrological dynamics. We developed a reactive transport model that integrates methane production with hydrodynamic and ebullitive pathways and coupled it with a basin-scale groundwater flow model to simulate methane emissions across scales. By incorporating key factors such as vertical hydrological exchange flow (VHEF), particulate organic carbon availability, sediment properties, and temperature sensitivity, our model captures the spatiotemporal variability of methane ebullition at both the site and basin scales. Our results reveal that methane ebullition is strongly modulated by VHEF, with lower flow rates promoting methane accumulation and subsequent ebullition. Sensitivity analyses underscore nonlinear responses of methane fluxes to environmental drivers. Furthermore, these findings emphasize the critical roles of sediment composition, hydrological exchange, and environmental conditions in shaping methane dynamics. Overall, this work advances our understanding of riverine methane emissions and offers insights for guiding climate models and mitigation strategies.
Highlights: • The dynamic recrystallization process is enhanced by the operation of slip. • Continuous dynamic recrystallization is promoted by the rotation of grains. • Texture induced hardening hides the softening induced by dynamic recrystallization. - Abstract: The present study investigated the influence of the initial orientation on the dynamic recrystallization (DRX) behavior of a Zr-1Sn-0.3Nb alloy. A hot-rolled and annealed Zr sheet was compressed along two directions: along the normal direction so that the grains' -axis was nearly parallel to the loading direction (0° sample) and along the transverse direction so that the grains' -axis was nearly perpendicular to the loading direction (90° sample). The samples were compressed at 700 °C at a strain rate of 1 s{sup −1}. The microstructures at different strains were characterized by the electron backscatter diffraction (EBSD) technique, and conventional dislocation analysis using transmission electron microscope (TEM) was performed. A threshold value of grain orientation spread (GOS) equaled to 5° was used to distinguish the dynamically recrystallized grains from the deformed matrix. The results revealed that the DRX behavior strongly depended on the initial orientation. The Schmid factor analysis and TEM observation confirmed that pyramidal slip operated from the first stage of deformation in the 0° sample but not in the 90° sample. For the 0° sample, in the early and medium stages of deformation, due to the high stored energy caused by the operation of pyramidal slip, DDRX was mainly contributed to the formation of new fine grains. However, in the later stage of deformation, the DRX mechanism changed from DDRX to CDRX. In the 90° sample, although DDRX featured by grain boundary bulging occurred, the main DRX mechanism was CDRX in the whole deformation processing. Moreover, texture induced hardening in the early stage of deformation hides the softening induced by DDRX.
Research was performed in atmospheric, dynamical, and thermodynamical processes and in other disciplines necessary to accomplish the following tasks: develop procedures for combining generalized radiative transfer codes with dynamic atmospheric model codes; perform diagnostic analysis of atmospheric processes to gain a better understanding of the evolution and development of mesoscale circulation systems and their precipitation structures; and to develop algorithms and software necessary to graphically display diagnostic sets on the MSFC McIDAS and EADS to facilitate scientific study and sensor capability evaluation. Research activities during this reporting period are detailed.
Fuel consumption can be improved by reducing car weight with substitution of aluminum and steel parts with magnesium (Mg). Magnesium formability at room temperature is limited due to strong basal texture generated prior processing. Shear band nucleation, observed under conditions in which dynamic strain aging (DSA), have been attributed to be responsible for texture weakening in dilute Mg – Rare Earths (RE) alloys. A low–cost substitution of RE is calcium (Ca) with similar atomic size. It is hypothesized that deformation of Mg – Ca alloys under DSA conditions improves Mg formability. In this study, Mg–Ca and Mg–Ca–Zn alloys were characterized using optical microscopy, XRD, and SEM/EDS. Compression testing was performed between 200 and 300C at different strain rates to observe DSA behavior. This work was performed under DOE Award Number DE-EE0007756.