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This slide presentation discusses a method of inverse design for low sonic boom using adjoint-based gradient computations. It outlines a method for shaping a configuration in order to match a prescribed near-field signature.
Measurement of the photocurrent as a function of the thickness of a light absorber has been shown herein both theoretically and experimentally to provide a method for determination of the minority-carrier diffusion length of a sample. To perform the measurement, an illuminated spot of photons with an energy well above the band gap of the material was scanned along the thickness gradient of a wedge-shaped, rear-illuminated semiconducting light absorber. Photogenerated majority carriers were collected through a back-side transparent ohmic contact, and a front-side liquid or Schottky junction collected the photogenerated minority carriers. Calculations showed that the diffusion length could be evaluated from the exponential variation in photocurrent as a function of the thickness of the sample. Good agreement was observed between experiment and theory for a solid-state silicon Schottky junction measured using this method. As an example for the application of the technique to semiconductor/liquid-junction photoelectrodes, the minority-carrier diffusion length was determined for graded thickness, sputtered tungsten trioxide and polished bismuth vanadate films under back-illumination in contact with an aqueous electrolyte. Furthermore, this wedge technique does not require knowledge of the spectral absorption coefficient, doping, or surface recombination velocity of the sample.
The hierarchical organization of microbial ecosystems determines the rates of processes that shape Earth's environment, define the stage upon which major evolutionary events occurred, and create biosignatures in sediments and atmospheres. In cyanobacterial mats, oxygenic photosynthesis provides energy, organic substrates and oxygen to the ecosystem. Incident light changes with depth in the mat, both in intensity and spectral composition, and counteracting gradients of oxygen and sulfide shape the chemical microenvironment. A combination of benefits and hazards of light, oxygen and sulfide promotes the allocation of the various essential mat processes between light and dark periods and to various depths in the mat. Microliters produce hydrogen, small organic acids, nitrogen and sulfur species. Such compounds fuel a flow of energy and electrons in these ecosystems and thus shape interactions between groups of microorganisms. Coordinated observations of population distribution, abundance, and activity for an entire community are making fundamental questions in ecology accessible. These questions address those factors that sustain the remarkable diversity of microorganisms that are now being revealed by molecular techniques. These questions also target the processes that shape the various kinds of biosignatures that we will seek, both in ancient rocks from Earth and Mars, and in atmospheres of distant planets beyond our Solar System.
The hierarchical organization of microbial ecosystems determines the rates of processes that shape Earth#s environment, define the stage upon which major evolutionary events occurred, and create biosignatures in sediments and atmospheres. In cyanobacterial mats, oxygenic photosynthesis provides energy, organic substrates and oxygen to the ecosystem. Incident light changes with depth in the mat, both in intensity and spectral composition, and counteracting gradients of oxygen and sulfide shape the chemical microenvironment. A combination of benefits and hazards of light, oxygen and sulfide promotes the allocation of the various essential mat processes between light and dark periods and to various depths in the mat. Microbiota produce hydrogen, small organic acids, and nitrogen and sulfur species. Such compounds fuel a flow of energy and electrons in these ecosystems and thus shape interactions between groups of microorganisms. Coordinated observations of population distribution, abundance, and activity for an entire community are making fundamental questions in ecology accessible. These questions address those factors that sustain the remarkable diversity of microorganisms that are now being revealed by molecular techniques. These questions also target the processes that shape the various kinds of biosignatures that we will seek, both in ancient rocks from Earth and Mars, and in atmospheres of distant planets beyond our Solar System.
Understanding as-solidified grain structure development during constrained (G 0) alloy solidification conditions is a necessary component of understanding the larger process-microstructure relationships during additive manufacturing (AM) processing. This study applies a cellular automata (CA) model, for static solidification velocities and thermal gradients on the order of those expected in AM melt pools, to investigate grain shape development across ranges of input parameters governing temperature field evolution, nucleation, and growth. Variation in nucleated grain shape from columnar to equiaxed as a function of thermal gradient and nucleation density is modeled with CA and verified against the established transition model of Hunt and Gaumann. Furthermore, while thermal conditions and nucleation density are shown to have the largest roles on microstructure development, the sensitivity of grain structure was very unevenly distributed across parameter space. In particular, it was found that microstructure is very sensitive to mean nucleation undercooling and the interfacial response function in process space regimes near grain structure transitions, but entirely controlled by a combination of thermal gradient, solidification velocity, and nucleation density away from such transitions. The understanding of grain shape sensitivity obtained through CA modeling, particularly at large thermal gradient and nucleation density, will be necessary for accurate microstructure prediction during the extreme processing conditions and large input parameter uncertainty common to AM.
Many problems in aerodynamic design can be characterized by smooth and convex objective functions. This motivates the use of gradient-based algorithms, particularly for problems with a large number of design variables, to efficiently determine optimal shapes and configurations that maximize aerodynamic performance. Accurate and efficient computation of the gradient, however, remains a challenging task. In optimization problems where the number of design variables dominates the number of objectives and flow- dependent constraints, the cost of gradient computations can be significantly reduced by the use of the adjoint method. The problem of aerodynamic optimization using the adjoint method has been analyzed and validated for both structured and unstructured grids. The method has been applied to design problems governed by the potential, Euler, and Navier-Stokes equations and can be subdivided into the continuous and discrete formulations. Giles and Pierce provide a detailed review of both approaches. Most implementations rely on grid-perturbation or mapping procedures during the gradient computation that explicitly couple changes in the surface shape to the volume grid. The solution of the adjoint equation is usually accomplished using the same scheme that solves the governing flow equations. Examples of such code reuse include multistage Runge-Kutta schemes coupled with multigrid, approximate-factorization, line-implicit Gauss-Seidel, and also preconditioned GMRES. The development of the adjoint method for aerodynamic optimization problems on Cartesian grids has been limited. In contrast to implementations on structured and unstructured grids, Cartesian grid methods decouple the surface discretization from the volume grid. This feature makes Cartesian methods well suited for the automated analysis of complex geometry problems, and consequently a promising approach to aerodynamic optimization. Melvin e t al. developed an adjoint formulation for the TRANAIR code, which is based on the full-potential equation with viscous corrections. More recently, Dadone and Grossman presented an adjoint formulation for the Euler equations. In both approaches, a boundary condition is introduced to approximate the effects of the evolving surface shape that results in accurate gradient computation.
The project succeeded in producing crack-free Bismuth Telluride thermoelectric parts with density exceeding 98% through laser powder bed fusion (LPBF) additive manufacturing (AM). This greatly exceeded the highest previously reported density of 88% and is the highest among all semiconducting materials processed by LPBF. The additively manufactured material shows comparable Seebeck coefficient as conventional form and can be made into complex geometries with reduced material loss. On the other hand, measured properties are dramatically sensitive to the AM process parameters used, such that with identical composition, the Seebeck coefficient can be controllably tuned from +120 µV/K to -207 µV/K, which means the material switches between an n-type to a p-type semiconductor depending on processing. These changes are accompanied by significant differences in the as-processed microstructure due to rapid solidification. A machine learning protocol was developed and greatly reduced the experimental burden of the project, reducing the typical process optimization period of 2 years to 6 months. The project was fully successful in the objective of producing defect-free, complex geometry of bismuth-telluride parts through LPBF, but only partially successful in achieving performance goals. First, cost reduction of manufacturing, as measured by material waste, was successfully reduced by up to 70% compared to conventional manufacturing methods. This exceeded the proposed 30% reduction in materials waste needed to reach the 20% cost reduction goal of the project. On the other hand, the device performance, as measured by Seebeck coefficient, failed to reach the 40% improvement in efficiency. Rather, we observe comparable Seebeck coefficient between AM samples and conventionally processed counterparts. The device-level efficiency improvement does exceed 40% for complex geometry samples due to shape-induced increase in temperature gradients, but this was not the originally proposed metric. The machine learning approach developed in this project greatly accelerated the process optimization and can be adopted for fast development of AM processing parameters for other brittle and otherwise difficult-to-print materials. For the public, we deliver an efficient and widely adoptable process for incorporating waste-heat harvesting thermoelectric devices in both industrial and commercial heat exchangers. The geometric flexibility allows the capturing device to conform to the shape of the heat source to improve the system-level conversion efficiency. The technique can be deployed on any commercial LBPF systems with zero modifications, thus poses minimal adoption barrier for any manufacturer that already employed AM technology. Beyond bismuth-telluride, the machine-learning guided optimization protocol can be used in the future to reduce both the time and cost of process development for AM of other energy conversion and harvesting materials.
Chemical pollution mixtures enter aquatic environments and interact with microorganisms in eclectic ways with disparate consequences for microbial ecosystem services. Can using a thermodynamic framework help to determine the net influence of a chemical mixture on the functional capacity of benthic microbial communities? In this study, we examined this question by comparing benthic stream microbial communities exposed to a gradient of neutral-alkaline coalmine effluent. Using a combination of approaches (metagenomics, quantitative polymerase chain reaction [qPCR], and functional assays), we show that functional genes and pathways of microbial communities growing in mine effluent differed in composition, but not diversity. The majority of functional genes and pathways that changed decreased at sites exposed to mine effluent, resulting in lower abundances of nitrogenase and methanogen genes and fermentation pathways. However, selenate reductase gene abundance increased with water and sediment concentration of an ecologically important contaminant at mined sites: selenium. Denitrification genes nosZ and nirK differed between sites: metagenome-based nosZ increased with dissolved nitrate concentration and qPCR-based nirK had a hump-shaped pattern across the mining gradient. Osmoprotectant gene abundance did not change. Extracellular enzyme assays and alkaline phosphatase gene relative abundance suggested that mined stream microbial communities may be constrained by phosphorus bioavailability. Subsidies and stressors related to changes in a set of functional genes and pathways, but differences were not consistently predictable using thermodynamic expectations. Laslty, this suggests that pairing hypotheses for expected subsidies and stressors with post hoc explorations can yield valuable directions for future study of how microbial functional capacity responds to pollutant mixtures.
The recent interest in High Speed Civil Transport (HSCT) has resulted in renewed research studies of optimized supersonic cruise transport configurations. Incorporation of flow viscosity effects in the design process of such a supersonic wing is currently under investigation. This may lead to more accurate problem formulations and, in turn, greater aerodynamic efficiency than can be obtained by the traditional, inviscid, linear theories. In this context, for a design code to be a candidate for a complex optimization problem, such as three-dimensional viscous supersonic wing design, it should be validated using simpler building-block shapes. To optimize the shape of a supersonic wing, an automated method that also includes higher fidelity to the flow physics is desirable. With this impetus, an aerodynamic optimization methodology incorporating Navier-Stokes equations and sensitivity analysis had been previously developed. Prior to embarking upon the wing design task, the present investigation concentrated on testing the flexibility of the methodology, and the identification of adequate problem formulations, by defining two-dimensional, cost-effective test cases. Starting with two distinctly different initial airfoils, two independent shape optimizations resulted in shapes with very similar features. Secondly, the normal section to the subsonic portion of the leading edge, which had a high normal angle-of-attack, was considered. The optimization resulted in a shape with twist and camber, which eliminated the adverse pressure gradient, hence, exploiting the leading-edge thrust. The wing section shapes obtained in all the test cases had the features predicted by previous studies. Therefore, it was concluded that the flowfield analyses and the sensitivity coefficients were computed and fed to the present gradient-based optimizer correctly. Also, as a result of the present two-dimensional study, suggestions were made for problem formulations which should contribute to an effective wing shape optimization.
To improve the shape of a supersonic wing, an automated method that also includes higher fidelity to the flow physics is desirable. With this impetus, an aerodynamic optimization methodology incorporating thin-layer Navier-Stokes equations and sensitivity analysis had been previously developed. Prior to embarking upon the wind design task, the present investigation concentrated on testing the feasibility of the methodology, and the identification of adequate problem formulations, by defining two-dimensional, cost-effective test cases. Starting with two distinctly different initial airfoils, two independent shape optimizations resulted in shapes with similar features: slightly cambered, parabolic profiles with sharp leading- and trailing-edges. Secondly, the normal section to the subsonic portion of the leading edge, which had a high normal angle-of-attack, was considered. The optimization resulted in a shape with twist and camber which eliminated the adverse pressure gradient, hence, exploiting the leading-edge thrust. The wing section shapes obtained in all the test cases had the features predicted by previous studies. Therefore, it was concluded that the flowfield analyses and sensitivity coefficients were computed and fed to the present gradient-based optimizer correctly. Also, as a result of the present two-dimensional study, suggestions were made for the problem formulations which should contribute to an effective wing shape optimization.
Steep density gradients generally lead to improved plasma performance in the neoclassically optimized stellarator W7-X. This is evident in the global energy confinement time as well as in the ion temperature and can be explained by a strong reduction of the ion temperature gradient turbulence. Such conditions can experimentally be realized by several methods: injection of cryogenic hydrogen pellets, appropriate combination of neutral beam and electron cyclotron resonance heating (ECRH) and, in some cases, with low power of ECRH after preconditioning of the first wall. The duration of the improved phases is determined by the ability to sustain the steep density gradient, by technical limitations of the involved systems and, eventually, by the plasma stability. This paper gives an overview of relevant experimental results and presents example discharges where the improved confinement conditions could be extended to multiple seconds: up to 4 s using neutral beam injection and from 14 to 40 s with steady state pellet injection. In these plasmas the turbulent thermal diffusivity is reduced by a factor of 3 to 4 in a broad radial range, which allows high ion temperatures of up to 3 keV at the densities of about 1.5 • 10 20 m −3 .
Purpose: To quantitatively compare low dose spillage outside of PTV edge in arc therapy modalities Methods: The machines used in the study are Tomotherapy Hi-Arc and Varian 21EX with millennium120 MLC. TPS are TomoPlaning and RayStation for VMAT, respectively. The phantom is a 30cm diameter cylindrical solid water (TOMOTHERAPY, TOMOPHANTOM ASSY). The PTV is 4cm length with ellipsoidal sectional shape with major axis=5cm, minor axis=3cm in the axial plane and reversed in the coronal plane. The PTV volume is created with interpolation. It is located at the center of the phantom. The prescribed dose is 1000x5 cGy to 95% the PTV. The isocenter is set co-centered with the PTV. EBT-3 film was used to measure iso-dose lines at the center plane. Film dosimetry is performed with the RIT, v6.2. Results: the study shows: (1) dose falloff gradient is usually uneven, depending on the PTV shape in the gantry rotation plane. For an elliptical shape, the low dose spillage is wider in the minor axis direction than that in the major axis direction. The more a shape is closer to circular, the more even gradient is all directions; (2)for a circular shape (CAX plane in this study), the maximum dose in % of Rx dose at 2cm from PTV is 55% for Tomo, vs. 70% for VMAT (3) the most rapid dose falloff rang is between 95%–80% IDL for both modalities. Conclusion: Tomo has more rapid dose falloff outside of PTV. In some areas, the gradient is double for Tomo helical than that for LINAC VMAT at same points. Future work will examine the differences between optimization of doses and inherent delivery limitations.
We consider a classical aerodynamic shape optimization problem subject to the compressible Euler flow equations. The gradient of the cost functional with respect to the shape variables is derived with the adjoint method at the continuous level. The Hessian (second order derivative of the cost functional with respect to the shape variables) is approximated also at the continuous level, as first introduced by Arian and Ta'asan (1996). The approximation of the Hessian is used to approximate the Newton step which is essential to accelerate the numerical solution of the optimization problem. The design space is discretized in the maximum dimension, i.e., the location of each point on the intersection of the computational mesh with the airfoil is taken to be an independent design variable. We give numerical examples for 86 design variables in two different flow speeds and achieve an order of magnitude reduction in the cost functional at a computational effort of a full solution of the analysis partial differential equation (PDE).
Extrusion of unhomogenized castings of 7075 aluminum (Al) alloy has been accomplished using shear assisted processing and extrusion (ShAPE). The simultaneous plastic deformation and heat generation during ShAPE rapidly fracture and dissolve interdendritic and intragranular secondary phases of Al-Zn-Mg-Cu, accomplishing homogenization in seconds rather than many hours in a furnace prior to extrusion. ShAPE thereby eliminates the energy-intensive and time-consuming homogenization step required to prepare as-cast microstructures for conventional extrusion. Concurrently, extensive grain refinement occurs due to gradient activation of dynamic recrystallization during ShAPE, which facilitates a threefold increase in extrusion speed compared to the conventional extrusion method. Evident enhancement of the mechanical properties of ShAPE+T6 samples is achieved, compared to the ASTM standard values for conventional extrusion products. The microstructural evolution pathway, involving the processes of grain refinement and secondary particle dissolution, is explained using scanning and transmission electron microscopy.
Viruses play an important role in the ecology and biogeochemistry of marine ecosystems. Beyond mortality and gene transfer, viruses can reprogram microbial metabolism during infection by expressing auxiliary metabolic genes (AMGs) involved in photosynthesis, central carbon metabolism, and nutrient cycling. While previous studies have focused on AMG diversity in the sunlit and dark ocean, less is known about the role of viruses in shaping metabolic networks along redox gradients associated with marine oxygen minimum zones (OMZs). Here, we analyzed relatively quantitative viral metagenomic datasets that profiled the oxygen gradient across Eastern Tropical South Pacific (ETSP) OMZ waters, assessing whether OMZ viruses might impact nitrogen (N) cycling via AMGs. Identified viral genomes encoded six N-cycle AMGs associated with denitrification, nitrification, assimilatory nitrate reduction, and nitrite transport. The majority of these AMGs (80%) were identified in T4-like Myoviridae phages, predicted to infect Cyanobacteria and Proteobacteria, or in unclassified archaeal viruses predicted to infect Thaumarchaeota. Four AMGs were exclusive to anoxic waters and had distributions that paralleled homologous microbial genes. Together, these findings suggest viruses modulate N-cycling processes within the ETSP OMZ and may contribute to nitrogen loss throughout the global oceans thus providing a baseline for their inclusion in the ecosystem and geochemical models.
We study systematics associated with estimating simple stellar population (SSP) parameters – age, metallicity [M/H], α-enhancement [α/Fe], and initial mass function (IMF) shape – and associated M * /L gradients, of elliptical slow rotators (E-SRs), fast rotators (E-FRs), and S0s from stacked spectra of galaxies in the MaNGA survey. These systematics arise from (i) how one normalizes the spectra when stacking; (ii) having to subtract emission before estimating absorption line strengths; (iii) the decision to fit the whole spectrum or just a few absorption lines; (iv) SSP model differences (e.g. isochrones, enrichment, IMF). The MILES+Padova SSP models, fit to the H β , 〈Fe〉, TiO 2SDSS , and [MgFe] Lick indices in the stacks, indicate that out to the half-light radius R e : (a) ages are younger and [α/Fe] values are lower in the central regions but the opposite is true of [M/H]; (b) the IMF is more bottom-heavy in the center, but is close to Kroupa beyond about R e /2; (c) this makes M * /L about 2 × larger in the central regions than beyond R e /2. While the models of Conroy et al. return similar [M/H] and [α/Fe] profiles, the age and (hence) M * /L profiles can differ significantly even for solar abundances and a Kroupa IMF; different responses to non-solar abundances and IMF parametrization further compound these differences. There are clear (model independent) differences between E-SRs, E-FRs, and S0s: younger ages and less enhanced [α/Fe] values suggest that E-FRs and S0s are not SSPs, but relaxing this assumption is unlikely to change their inferred M * /L gradients significantly.
We report that due to their non-volatility and intrinsic current integration capabilities, spintronic devices that rely on domain wall (DW) motion through a free ferromagnetic track have garnered significant interest in the field of neuromorphic computing. Although a number of such devices have already been proposed, they require the use of external circuitry to implement several important neuronal behaviors. As such, they are likely to result in either a decrease in energy efficiency, an increase in fabrication complexity, or even both. To resolve this issue, we have proposed three individual neurons that are capable of performing these functionalities without the use of an external circuitry. To implement leaking, the first neuron uses a dipolar coupling field, the second uses an anisotropy gradient, and the third uses shape variations of the DW track.
We present a Fixed-Field-Alternating (FFA) permanent magnet racetrack electron accelerator with energy range between 10-60 GeV for the future LHeC. Electron beam is brought back to the linac by the single beam line without requiring electric power REDUCING estimated wall power of 100 MW in the present LHeC design to a negligible power for arcs as the permanent magnets are used. The design is based on experience from the very successful commissioning of the Cornell University and Brookhaven National Laboratory Energy Recovery Test Accelerator ? ?CBETA?. The proposal supports sustainability efforts for LHeC by making a 'green' accelerator. It is an energy recovery linac with 99.9% energy efficiency and reduces the power consumption by using small permanent magnets. The FFA non-linear gradient design is a racetrack shape, where, as in the CBETA, the arcs are matched by adiabatic transition to the two (LHeC) or multiple straight sections. Two 10 GeV superconducting linacs are placed on both sides of the Interaction Region (IR) significantly reducing the power of synchrotron radiation loss.