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At least 1,495 records · Page 83

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NASA NTRSDate not supplied

Service Provider Agnostic Adaptive Coding and Modulation System Design

Commercial service providers (CSPs) are increasingly used to provide communications services to near-Earth science and exploration missions. CSPs commonly utilize modems that are designed to implement adaptive coding and modulation (ACM) in unique ways with modems from the same vendor. However, some missions cannot fly a matching vendor modem, either because the vendor only designs modems for terrestrial use, or the mission needs to fly a software defined radio. We present an ACM system design that allows missions to implement ACM on DVB-S2 compliant CSP links without needing to fly a modem from the same vendor the CSP uses. We implement and test our design in an emulated communications testbed. These tests demonstrate that our ACM system design can successfully adapt to link quality changes up to 6.12 dB/second.

Adaptive coding and modulation↗

NASA NTRSDate not supplied

Service Provider Agnostic Adaptive Coding and Modulation System Design

Adaptive coding and modulation↗

DOE OSTI2017

Adaptive Individual Blade Pitch Control of an Ocean Current Turbine for Load Reduction

A Direct Adaptive Disturbance Rejection (DADR) control algorithm is evaluated using a numer-ical simulation of an Ocean Current Turbine (OCT) for its ability to minimize the cyclic loadings on the rotor blades caused by current shear. This control algorithm reduces these cyclic loadings by individually altering the pitch angles of the rotor blades as a function of rotor rotation angle. The OCT numerical model represents a system with a single 3 bladed 20 meter diameter rotor operated in the Gulf Stream off the coast of Ft. Lauderdale, Florida for mean and maximum measured current shear values of 0.004 and 0.03 (m/s)/m. The results indicate that the adaptive controller reduced the amplitude of the cyclic axial blade loads on a rigidly mounted and moored turbine by 91.18% and 92.3% in the mean current shear and by 94.12% and 81.88% in maximum current shear demonstrating the value of this controls approach.

adaptive control↗

DOE OSTI2024

Ad-Mat: Adaptations of Mature Manufacturing Strategies for Accelerated Redox Flow Battery Deployment

The concept of the Ad-Mat approach is to leverage existing adjacent markets across a broad scope of technologies in order to reduce the manufacturing learning curve and ultimately accelerate redox flow battery (RFB) deployment at scale. Lithium-ion batteries (LIBs) are currently the dominant energy storage technology, and they came to technological maturity under unique market conditions when there was no meaningful competition in the consumer electronic and electric vehicle (EV) space. Today, alternative chemistries that may be technologically better-suited for long-duration storage applications are experiencing a high barrier to entry. This is in large part due to the substantial bias towards the scaled-up production and supply chain that now exists for LIBs. In the case of RFBs in particular, numerous analyses have suggested that RFBs should theoretically have a much lower system cost than LIBs - however, this relies on a mature and competitive manufacturing landscape, which has been extremely challenging to achieve for both flow batteries and other LIB competitors. At the moment, LIB alternatives tend to have isolated small-scale manufacturing pathways, which preclude the economies of scale that would be required to compete with the mature LIB industry. In the present state of the industry, niche manufacturing tools and approaches have evolved to support each alternative technology, such that there is substantial replication and duplication in effort. Continuing to pursue a strategy of isolated manufacturing processes/approaches for each LIB-alternative may never allow for at-scale deployment. In order for RFBs to meaningfully compete with LIBs in the realm of LDES, a new disruptive approach based on cross-industry learning and coordination is needed - and this is exactly what our Ad-Mat concept aims to tackle. In this re-envisioned manufacturing landscape, tools and processes from mature industries can be adapted and deployed across the range of alternative energy storage technologies. Adapting tools, equipment, processes, and industrial learning from mature industries to meet the technological requirements of RFBs would open new markets for existing OEMs in adjacent industries, would prevent unnecessary duplication and re-development, would improve efficiency across the manufacturing chain, and would ultimately support reduced costs and accelerated deployment of RFBs at scale.

adaptive manufacturing↗

DOE OSTI2024

Enabling Scale-Up Through Multi-Fidelity Adaptive Computing

We present ideas from our ongoing work in adaptive computing - an optimization framework that allows us to strategically deploy various fidelity level experiments and simulations to guide decision making. The framework aims to enable uncertainty quantified scale-up of simulations and experiments, which causes increased complexity. A key feature of the framework is the integration of user-specified local model trustworthiness estimates. Adaptive sampling strategies allow us to optimally exploit the multiple fidelity level information and trustworthiness measures to arrive at the best decisions within a highly limited budget of objective function evaluations.

adaptive sampling↗

DOE OSTI2016

An adaptive lattice Boltzmann scheme for modeling two-fluid-phase flow in porous medium systems

In this paper, we formulate a multiple-relaxation-time (MRT) lattice-Boltzmann method (LBM) to simulate two-fluid-phase flow in porous medium systems. The MRT LBM is applied to simulate the displacement of a wetting fluid by a nonwetting fluid in a system corresponding to a microfluidic cell. Analysis of the simulation shows widely varying time scales for the dynamics of fluid pressures, fluid saturations, and interfacial curvatures that are typical characteristics of such systems. Displacement phenomena include Haines jumps, which are relatively short duration isolated events of rapid fluid displacement driven by capillary instability. An adaptive algorithm is advanced using a level-set method to locate interfaces and estimate their rate of advancement. Because the displacement dynamics are confined to the interfacial regions for a majority of the relaxation time, the computational effort is focused on these regions. The proposed algorithm is shown to reduce computational effort by an order of magnitude, while yielding essentially identical solutions to a conventional fully coupled approach. Finally, the challenges posed by Haines jumps are also resolved by the adaptive algorithm. Possible extensions to the advanced method are discussed.

42 ENGINEERING↗

DOE OSTI2015

Divergence and gene flow among Darwin's finches: A genome‐wide view of adaptive radiation driven by interspecies allele sharing

A recent analysis of the genomes of Darwin's finches revealed extensive interspecies allele sharing throughout the history of the radiation and identified a key locus responsible for morphological evolution in this group. The radiation of Darwin's finches on the Galápagos archipelago has long been regarded as an iconic study system for field ecology and evolutionary biology. Coupled with an extensive history of field work, these latest findings affirm the increasing acceptance of introgressive hybridization, or gene flow between species, as a significant contributor to adaptive evolution. Here, we review and discuss these findings in relation to both classical work on Darwin's finches and contemporary work showing similar evolutionary signatures in other biological systems. The continued unification of genomic data with field biology promises to further elucidate the molecular basis of adaptation in Darwin's finches and well beyond.

Palmer, Daniela H.↗

DOE OSTI2018

Enzymatic Adaptation of Podospora anserina to Different Plant Biomass Provides Leads to Optimized Commercial Enzyme Cocktails

As a late colonizer of herbivore dung, Podospora anserina has evolved an enzymatic machinery to degrade the more recalcitrant fraction of plant biomass, suggesting a great potential for biotechnology applications. The authors investigated its transcriptome during growth on two industrial feedstocks, soybean hulls (SBH) and corn stover (CS). Initially, CS and SBH results in the expression of hemicellulolytic and amylolytic genes, respectively, while at later time points a more diverse gene set is induced, especially for SBH. Substrate adaptation is also observed for carbon catabolism. Overall, SBH resulted in a larger diversity of expressed genes, confirming previous proteomics studies. The results not only provide an in depth view on the transcriptomic adaptation of P. anserina to substrate composition, but also point out strategies to improve saccharification of plant biomass at the industrial level.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

In‐memory integration of existing software components for parallel adaptive unstructured mesh workflows

Summary Reliable mesh‐based simulations are needed to solve complex engineering problems. Mesh adaptivity can increase reliability by reducing discretization errors but requires multiple software components to exchange information. Often, components exchange information by reading and writing a common file format. This file‐based approach becomes a problem on massively parallel computers where filesystem bandwidth is a critical performance bottleneck. Our approach using data streams and component interfaces avoids the filesystem bottleneck. In this paper, we present these techniques and their use for coupling mesh adaptivity to the PHASTA computational fluid dynamics solver, the Albany multi‐physics framework, and the Omega3P linear accelerator frequency analysis applications. Performance results are reported on up to 16,384 cores of an Intel Knights Landing‐based system.

Smith, Cameron W.↗

DOE OSTI2016

A parallel adaptive numerical method with generalized curvilinear coordinate transformation for compressible Navier–Stokes equations

A fourth-order finite-volume method for solving the Navier–Stokes equations on a mapped grid with adaptive mesh refinement is proposed, implemented, and demonstrated for the prediction of unsteady compressible viscous flows. The method employs fourth-order quadrature rules for evaluating face-averaged fluxes. Our approach is freestream preserving, guaranteed by the way of computing the averages of the metric terms on the faces of cells. The standard Runge–Kutta marching method is used for time discretization. Solutions of a smooth flow are obtained in order to verify that the method is formally fourth-order accurate when applying the nonlinear viscous operators on mapped grids. Solutions of a shock tube problem are obtained to demonstrate the effectiveness of adaptive mesh refinement in resolving discontinuities. A Mach reflection problem is solved to demonstrate the mapped algorithm on a non-rectangular physical domain. The simulation is compared against experimental results. Future work will consider mapped multiblock grids for practical engineering geometries.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Adaptive downstream tensorial eddy viscosity for hybrid large‐eddy simulations‐Reynolds‐averaged‐Navier–Stokes simulations

An adaptive method is developed to improve the accuracy of eddy‐viscosity Reynolds‐averaged‐Navier–Stokes (RANS) model in hybrid large‐eddy simulations (LES)‐RANS simulations by using available upstream LES results. The method first gets the tensorial eddy viscosity from the upstream LES solution at the LES‐RANS interface and then uses that information to improve the downstream RANS model by invoking the weak‐equilibrium assumption. The proposed method was evaluated via two test problems—flow in a channel and over a periodic hill. Results obtained show the proposed approach to increase the accuracy and stability of hybrid LES‐RANS simulations. Since the modification of the downstream RANS model is based on the tensorial eddy viscosity from the upstream LES solution, the method is adaptive to the problem being studied.

Zhang, Wanjia↗

DOE OSTI2022

Hybrid large-eddy simulation with adaptive downstream anisotropic eddy viscosity model

Turbulence pervades most flows of engineering interest, and its prediction remains a challenge on both accuracy and cost. One promising predictive approach that reduces cost combines large-eddy simulation (LES) with simulation based on Reynolds averaged Navier–Stokes equations (RANS). This study presents a method to overcome stability and accuracy issues associated with these hybrid LES-RANS methods. The method developed involves extracting the Reynolds stresses from the upstream LES solution and then using that information to convert the downstream RANS model from a scalar eddy-viscosity model to an anisotropic nonlinear eddy-viscosity model. The method developed differs from the downstream tensorial eddy-viscosity model by being independent of the coordinate system. The method developed was evaluated by computing film cooling of a flat plate with the coolant injected through one row of circular holes. Results obtained show instabilities at the LES-to-RANS interface to be eliminated. Also, the method developed yielded solutions that compare reasonably well with those from LES, even though a significant portion of the flow is computed by the adapted anisotropic RANS model instead of LES, which significantly reduced the number of grid points and computational time needed. Since modification of the downstream RANS model is based on information extracted from the upstream LES solution, the method developed is adaptive to the problem being studied.

42 ENGINEERING↗

DOE OSTI2023

Caspian Tern Management to Increase Survival of Juvenile Salmonids in the Columbia River Basin: Progress and Adaptive Management Considerations

Abstract Predation by Caspian terns Hydroprogne caspia is a factor limiting the recovery of some Endangered Species Act-listed populations of salmonids from the Columbia River basin, especially steelhead Oncorhynchus mykiss. This prompted the development and implementation of two separate management plans, one in the Columbia River estuary and the other in the Columbia Plateau region, to reduce the impact of Caspian tern predation on smolt survival. Caspian terns nesting at managed breeding colonies within the basin were relocated to alternative nesting islands created for terns outside the basin. Both plans were successful in significantly reducing smolt losses to Caspian terns nesting at managed sites; however, new developments have led to regression in smolt survival gains associated with tern management. Adaptive management to prevent terns at managed colonies from relocating to nest elsewhere in the basin and to improve nesting opportunities for Caspian terns outside the basin are needed to maximize the survival benefits to Endangered Species Act-listed salmonids from management. Adaptive management is also necessary to ensure the long-term viability of the Pacific Flyway population of Caspian terns, whose breeding population has declined by more than 50% since the two management plans were implemented.

Collis, Ken↗

DOE OSTI2023

Adaptive changes in sexual behavior in the high–risk population in response to human monkeypox transmission in Canada can help control the outbreak: Insights from a two–group, two–route epidemic model

Monkeypox, a zoonotic disease, is emerging as a potential sexually transmitted infection/disease, with underlying transmission mechanisms still unclear. We devised a risk-structured, compartmental model, incorporating sexual behavior dynamics. We compared different strategies targeting the high-risk population: a scenario of control policies geared toward the use of condoms and/or sexual abstinence (robust control strategy) with risk compensation behavior change, and a scenario of control strategies with behavior change in response to the doubling rate (adaptive control strategy). Monkeypox's basic reproduction number is 1.464, 0.0066, and 1.461 in the high-risk, low-risk, and total populations, respectively, with the high-risk group being the major driver of monkeypox spread. Policies imposing condom use or sexual abstinence need to achieve a 35% minimum compliance rate to stop further transmission, while a combination of both can curb the spread with 10% compliance to abstinence and 25% to condom use. With risk compensation, the only option is to impose sexual abstinence by at least 35%. Adaptive control is more effective than robust control where the daily sexual contact number is reduced proportionally and remains constant thereafter, shortening the time to epidemic peak, lowering its size, facilitating disease attenuation, and playing a key role in controlling the current outbreak.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

Limited‐memory adaptive snapshot selection for proper orthogonal decomposition

Summary Reduced order models are useful for accelerating simulations in many‐query contexts, such as optimization, uncertainty quantification, and sensitivity analysis. However, offline training of reduced order models (ROMs) can have prohibitively expensive memory and floating‐point operation costs in high‐performance computing applications, where memory per core is limited. To overcome this limitation for proper orthogonal decomposition, we propose a novel adaptive selection method for snapshots in time that limits offline training costs by selecting snapshots according an error control mechanism similar to that found in adaptive time‐stepping ordinary differential equation solvers. The error estimator used in this work is related to theory bounding the approximation error in time of proper orthogonal decomposition‐based ROMs, and memory usage is minimized by computing the singular value decomposition using a single‐pass incremental algorithm. Results for a viscous Burgers' test problem demonstrate convergence in the limit as the algorithm error tolerances go to zero; in this limit, the full‐order model is recovered to within discretization error. A parallel version of the resulting method can be used on supercomputers to generate proper orthogonal decomposition‐based ROMs, or as a subroutine within hyperreduction algorithms that require taking snapshots in time, or within greedy algorithms for sampling parameter space. Copyright © 2016 John Wiley & Sons, Ltd.

Oxberry, Geoffrey M.↗

DOE OSTI2023

Deformation Rate‐Adaptive Conducting Polymers and Composites

Abstract Materials are more easily damaged during accidents that involve rapid deformation. Here, a design strategy is described for electronic materials comprised of conducting polymers that defies this orthodox property, making their extensibility and toughness dynamically adaptive to deformation rates. This counterintuitive property is achieved through a morphology of interconnected nanoscopic core–shell micelles, where the chemical interactions are stronger within the shells than the cores. As a result, the interlinked shells retain material integrity under strain, while the rate of dissociation of the cores controls the extent of micelle elongation, which is a process that adapts to deformation rates. A prototype based on polyaniline shows a 7.5‐fold increase in ultimate elongation and a 163‐fold increase in toughness when deformed at increasing rates from 2.5 to 10 000% min −1 . This concept can be generalized to other conducting polymers and highly conductive composites to create “self‐protective” soft electronic materials with enhanced durability under dynamic movement or deformation.

Hernandez, Victor↗

DOE OSTI2018

Adaptive mesh refinement in stress-constrained topology optimization

We present a topology structural optimization framework with adaptive mesh refinement and stress-constraints. Finite element approximation and geometry representation benefit from such refinement by enabling more accurate stress field predictions and greater resolution of the optimal structural boundaries. We combine a volume fraction filter to impose a minimum design feature size, the RAMP penalization to generate “black-and-white designs” and a RAMP-like stress definition to resolve the “stress singularity problem.” Regions with stress concentrations dominate the optimized design. As such, rigorous simulations are required to accurately approximate the stress field. To achieve this goal, we invoke a threshold operation and mesh refinement during the optimization. We do so in an optimal fashion, by applying adaptive mesh refinement techniques that use error indicators to refine and coarsen the mesh as needed. In this way, we obtain more accurate simulations and greater resolution of the design domain. We present results in two dimensions to demonstrate the efficiency of our method.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

A posteriori error estimation and adaptivity in hp virtual elements

An explicit and computable error estimator for the hp version of the virtual element method (VEM), together with lower and upper bounds with respect to the exact energy error, is presented. Such error estimator is employed to provide, following the approach of Melenk and Wohlmuth (Adv Comput Math 15(1–4):311–331, 2001), hp adaptive mesh refinements for very general polygonal meshes. In addition, a novel VEM hp Clément quasi-interpolant, instrumental for the a posteriori error analysis, is introduced. The performances of the adaptive method are validated by a number of numerical experiments.

97 MATHEMATICS AND COMPUTING↗