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Mass flow rate of gas evolution from burning solid rocket propellant during transient depressurization of combustion chamber
Safe and efficient operation of tokamak experiments depends on shot preparation prior to the experiment to maximize performance and avoid issues that are predictable consequences of known physics. The General Atomics TokSys toolbox is used to test and develop the plasma control system (PCS) on numerous tokamaks around the world. Tokamaks that use a version of the DIII-D PCS can connect it to a TokSys simulation and control a virtual version of the tokamak with the real PCS. Recent upgrades to the simulation include more detailed profile and transport modeling to support design and implementation of optimized scenarios. The simulation combines a module called “Profiles” that simulates the 1D profiles of density, pressure, and current and a module called “GSevolve'' that evolves the 2D Grad-Shafranov equilibrium. The “Profiles'' module primarily uses simplified models for fueling, heating, and current. The TRANSP code provides precomputed diffusion coefficients and heating/current drive profiles from radio-frequency and neutral beam sources for the scenarios being simulated. The fidelity of a simulation can be enhanced by analyzing it with TRANSP and making corrections to the precomputed values and iterating until convergence. Simulations of the National Spherical Torus Upgrade (NSTX-U) are presented. It is shown that the simulation reproduces the experimental profile evolution. Here, the simulation has also been upgraded to reproduce the experimental outcome at points of bifurcation. This is demonstrated with a simulation of vertical displacement in NSTX-U.
Here, an experimental investigation of swirl and wake strength influence on axisymmetric turbulent wake evolution was conducted. A novel wake generator design wire mounted in a wind tunnel test section with low free-stream turbulence produced wake Reynolds numbers based on momentum thickness and free-stream velocity in excess of 14000 and swirl numbers up to 0.4 with minimal blockage. Steady-state blade element momentum simulations of reference wind turbine designs indicated that wind turbines operate in the flow regimes studied, indicating the practical aspects of this work. Stereoscopic particle image velocimetry was used to acquire three components of velocity in the swirling wake at locations up to approximately ten diameters downstream. Quantitative measures of wake growth and decay were deduced using available equilibrium similarity scaling for the swirling wake. The results show an increase above 50% in growth and axial velocity decay rate constants over the range of swirl strength studied compared to those of the non-swirling wake. Tangential velocity decay constants were shown to decrease with swirl strength over the range of conditions studied. Notably, changes in wake strength have little influence on growth and decay rates when compared to changes in swirl strength for the flow regimes studied in this work.
Crystal plasticity models evolve a polycrystalline yield surface using meso-scale descriptions of deformation mechanisms. The activation of deformation mechanisms is governed by crystallography and a set of model parameters, which are typically calibrated through the fitting of mechanical data such as stress–strain curves and elastic lattice strains. Microstructural data such as phase fractions and texture evolution are used for verifying crystal plasticity parameters. In this study, we use a multi-objective genetic algorithm to identify hardening parameters from flow stress curves with an option to incorporate texture into the optimization approach. Robust, generalized objective functions are developed and used to identify sets of parameters pertaining to dislocation density-based hardening laws in visco-plastic and elasto-plastic self-consistent (VPSC and EPSC) homogenization models. First, the parameters are identified for pure Nb directly from texture using an objective function based on generalized spherical harmonics. Since texture evolution is driven by the relative contribution of active slip systems, the parameters governing the evolution of slip resistance ratios can be recovered from fitting discrete textures at a series of strains. Next, a comprehensive set of load reversal data for dual phase (DP) 780 steel is used to fit a hardening law and a back-stress law in EPSC. Finally, parameters pertaining to a complex hardening law for the evolution of slip and twinning in pure α-Ti are identified. Remarkably, using texture as an objective in combination with stress–strain objectives constrains the model of Ti to fully reproduce not only stress–strain and texture evolution but also hierarchical twinning measurements as a function of initial grain size and texture. Furthermore, given an appropriate model fit to representative experimental texture evolution, underlying twin volume fractions contributing to texture evolution can be predicted.
The propagation of high-energy X-rays or hot electrons have the potential to alter the initial conditions in experimental target designs, especially at material interfaces, for laser-driven inertial confinement fusion (ICF) and high-energy density (HED) experimental platforms. Hot-electron preheat can drastically modify the initial conditions of experimental targets used to study the deceleration-stage Rayleigh–Taylor instability (RTI) both with and without applied magnetic fields. Therefore, it is necessary to understand and quantify the impact of hot-electron preheat. The hydrodynamic (HD) capabilities in the Ares code are used to study the effects varying levels of preheat can have on RTI evolution. The experimental and computational studies presented in this work demonstrate that at high laser intensities of around or greater than 10 15 W cm −2 , there is hot-electron generation from laser plasma instabilities which induces substantial preheat and impacts the morphology of RTI evolution and even inhibits the intended RTI growth such that it is not observable experimentally. The necessity of better quantifying hot-electron induced preheat and mitigating its impact on such high-intensity direct-drive laser experiments in the future is discussed.
We describe the next-generation system for in situ characterization of a complex oxide thin film and heterostructure growth by pulsed laser deposition (PLD) using synchrotron hard X-rays. The system consists of a PLD chamber mounted on a diffractometer allowing both real-time surface X-ray diffraction (SXRD) and in situ hard X-ray photoelectron spectroscopy (HAXPES). HAXPES is performed in the incident X-ray energy range from 4 to 12 keV using a Scienta EW4000 electron energy analyzer mounted on the PLD chamber fixed parallel with the surface normal. In addition to the standard application mode of HAXPES for disentangling surface from bulk properties, the increased penetration depth of high energy photoelectrons is used for investigation of the electronic structure changes through thin films grown deliberately as variable thickness capping layers. Such heterostructures represent model systems for investigating a variety of critical thickness and dead layer phenomena observed at complex oxide interfaces. In this new mode of operation, in situ HAXPES is used to determine the electronic structure associated with unique structural features identified by real-time SXRD during thin film growth. The system is configured for using both laboratory excitation sources off-line and on-line operation at beamline 33-ID-D at the Advanced Photon Source. We illustrate the performance of the system by preliminary scattering and spectroscopic data on oxygen vacancy ordering induced perovskite-to-brownmillerite reversible phase transformation in La 2/3 Sr 1/3 MnO 3 films capped with oxygen deficient SrTiO 3–δ (100) layers of varying thickness.
The experimental phase diagram for liquid–liquid phase separation in submicrometer aerosol particles converges with theory as equilibration time is increased.
Prediction of material performance in fusion reactor environments relies on computational modelling, and will continue to do so until the first generation of fusion power plants come on line and allow long-term behaviour to be observed. In the meantime, the modelling is supported by experiments that attempt to replicate some aspects of the eventual operational conditions. In 2019, a group of leading experts met under the umbrella of the IEA to discuss the current position and ongoing challenges in modelling of fusion materials and how advanced experimental characterisation is aiding model improvement. This review draws from the discussions held during that workshop. Topics covering modelling of irradiation-induced defect production and fundamental properties, gas behaviour, clustering and segregation, defect evolution and interactions are discussed, as well as new and novel multiscale simulation approaches, and the latest efforts to link modelling to experiments through advanced observation and characterisation techniques.
RNA polymerase (RNAP) is emblematic of complex biological systems that control multiple traits involving trade-offs such as growth versus maintenance. Laboratory evolution has revealed that mutations in RNAP subunits, including RpoB, are frequently selected. However, we lack a systems view of how mutations alter the RNAP molecular functions to promote adaptation. We, therefore, measured the fitness of thousands of mutations within a region of rpoB under multiple conditions and genetic backgrounds, to find that adaptive mutations cluster in two modules. Mutations in one module favor growth over maintenance through a partial loss of an interaction associated with faster elongation. Mutations in the other favor maintenance over growth through a destabilized RNAP-DNA complex. The two molecular handles capture the versatile RNAP-mediated adaptations. Combining both interaction losses simultaneously improved maintenance and growth, challenging the idea that growth-maintenance tradeoff resorts only from limited resources, and revealing how compensatory evolution operates within RNAP.
A Boussinesq system is integrated numerically in three dimensions and time in a study of nonhydrostatic convection in the atmosphere. Simulation of cloud convection is achieved by the inclusion of parametrized effects of latent heat and small-scale turbulence. The results are compared with the cell structure observed in Rayleigh-Benard laboratory conversion experiments in air. At a Rayleigh number of 4000, the numerical model adequately simulates the experimentally observed evolution, including some prominent transients of a flow from a randomly perturbed initial conductive state into the final state of steady large-amplitude two-dimensional rolls. At Rayleigh number 9000, the model reproduces the experimentally observed unsteady equilibrium of vertically coherent oscillatory waves superimposed on rolls.
We present a study of the role played by realistic three-body forces in providing a reliable monopole component of the effective shell-model Hamiltonian. To this end, starting from a nuclear potential built up within the chiral perturbation theory, we derive effective shell-model Hamiltonians with and without the contribution of the three-body potential and compare the results of shell-model calculations with a set of observables that evidence shell-evolution properties. The testing ground of our investigation is nuclei belonging to the fp shell, since the shell-evolution towards shell closures in 48 Ca and 56 Ni provides a paradigm for shell-model Hamiltonians. Furthermore, our analysis shows that only by including contributions of the three-body force is the monopole component of the effective shell-model Hamiltonian then able to reproduce the experimental shell evolution towards and beyond the closure at N = 28.
Significance Increasing evidence suggests that evolutionary processes frequently shape ecological patterns; however, most microbiome studies thus far have focused on only the ecological responses of these communities. By using parallel field experiments and focusing in on a model soil bacterium, we showed that bacterial “species” are differentially adapted to local climates, leading to changes in their composition. Furthermore, we detected strain-level evolution, providing direct evidence that both ecological and evolutionary processes operate on annual timescales. The consideration of eco-evolutionary dynamics may therefore be important to understand the response of soil microbiomes to future environmental change.
Improving evolutionary forecasting requires progressing from studying repeated evolution of a single genotype under identical conditions to formulating broad principles. These principles should enable predictions of how similar species will adapt to similar selective pressures. Evolve-and-resequence experiments with multiple species allow testing forecasts on different biological levels and elucidating the causes for failed predictions. Here, we show that forecasts for adaptation to static culture conditions can be extended to multiple species by testing previous predictions for Pseudomonas syringae and Pseudomonas savastanoi. In addition to sequence divergence, these species differ in their repertoire of biofilm regulatory genes and structural components. Consistent with predictions, both species repeatedly produced biofilm mutants with a wrinkly spreader phenotype. Predominantly, mutations occurred in the wsp operon, with less frequent promoter mutations near uncharacterized diguanylate cyclases. However, mutational patterns differed on the gene level, which was explained by a lack of conservation in relative fitness of mutants between more divergent species. The same mutation was the most frequent for both species suggesting that conserved mutation hotspots can increase parallel evolution. This study shows that evolutionary forecasts can be extended across species, but that differences in the genotype–phenotype–fitness map and mutational biases limit predictability on a detailed molecular level.
Originally developed in bacterial and fungal models, Adaptive Laboratory Evolution (ALE) experimentally selects for targeted phenotypes by allowing cells containing beneficial random genetic mutations to replicate more quickly in the presence of environmental stress. When applied to microalgae, this technique has been used to increase growth rate, stress tolerance, substrate utilization, and product yield. This review discusses ALE experimental design parameters, and summarizes key results and lessons learned from recent microalgal ALE studies. By documenting the current state of the field, we provide insight on the ways microalgal ALE might be used to develop commercially viable biotechnology strains.
Directed evolution has revolutionized biomolecular engineering by applying cycles of mutation, amplification and selection to genes of interest (GOIs). However, classical directed evolution methods that rely on manually staged evolutionary cycles constrain the scale and depth of the evolutionary search that is possible. Here we describe genetic systems that achieve cycles of rapid mutation, amplification and selection fully inside living cells, enabling the continuous evolution of GOIs as cells grow. These systems advance the scale, evolutionary search depth, ease and overall power of directed evolution and access important new areas of protein evolution and engineering.
In rapidly adapting asexual populations, including many microbial pathogens and viruses, numerous mutant lineages often compete for dominance within the population. These complex evolutionary dynamics determine the outcomes of adaptation, but have been difficult to observe directly. Previous studies have used whole-genome sequencing to follow molecular adaptation; however, these methods have limited resolution in microbial populations. Here we introduce a renewable barcoding system to observe evolutionary dynamics at high resolution in laboratory budding yeast. We find nested patterns of interference and hitchhiking even at low frequencies. These events are driven by the continuous appearance of new mutations that modify the fates of existing lineages before they reach substantial frequencies. We observe how the distribution of fitness within the population changes over time, and find a travelling wave of adaptation that has been predicted by theory. We show that clonal competition creates a dynamical ‘rich-get-richer’ effect: fitness advantages that are acquired early in evolution drive clonal expansions, which increase the chances of acquiring future mutations. However, less-fit lineages also routinely leapfrog over strains of higher fitness. Finally, our results demonstrate that this combination of factors, which is not accounted for in existing models of evolutionary dynamics, is critical in determining the rate, predictability and molecular basis of adaptation.
The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), funded by the United States National Science Foundation, National Institutes of Health, and Department of Energy, supports structural biologists and Protein Data Bank (PDB) data users around the world. The RCSB PDB, a founding member of the Worldwide Protein Data Bank (wwPDB) partnership, serves as the US data center for the global PDB archive housing experimentally-determined three-dimensional (3D) structure data for biological macromolecules. As the wwPDB-designated Archive Keeper, RCSB PDB is also responsible for the security of PDB data and weekly update of the archive. RCSB PDB serves tens of thousands of data depositors (using macromolecular crystallography, nuclear magnetic resonance spectroscopy, electron microscopy, and micro-electron diffraction) annually working on all permanently inhabited continents. RCSB PDB makes PDB data available from its research-focused web portal at no charge and without usage restrictions to many millions of PDB data consumers around the globe. It also provides educators, students, and the general public with an introduction to the PDB and related training materials through its outreach and education-focused web portal. This review article describes growth of the PDB, examines evolution of experimental methods for structure determination viewed through the lens of the PDB archive, and provides a detailed accounting of PDB archival holdings and their utilization by researchers, educators, and students worldwide.
Abstract The fitness effects of all possible mutations available to an organism largely shape the dynamics of evolutionary adaptation. Yet, whether and how this adaptive landscape changes over evolutionary times, especially upon ecological diversification and changes in community composition, remains poorly understood. We sought to fill this gap by analyzing a stable community of two closely related ecotypes (“L” and “S”) shortly after they emerged within the E. coli Long-Term Evolution Experiment (LTEE). We engineered genome-wide barcoded transposon libraries to measure the invasion fitness effects of all possible gene knockouts in the coexisting strains as well as their ancestor, for many different, ecologically relevant conditions. We find consistent statistical patterns of fitness effect variation across both genetic background and community composition, despite the idiosyncratic behavior of individual knockouts. Additionally, fitness effects are correlated with evolutionary outcomes for a number of conditions, possibly revealing shifting patterns of adaptation. Together, our results reveal how ecological and epistatic effects combine to shape the adaptive landscape in a nascent ecological community.