More Like this

1. Experimental Testing and Numerical Modeling of Small-Scale Boat With Drag-Reducing Air-Cavity System

   https://doi.org/10.1115/FEDSM2021-62556  

   Collins, Jeffrey M. ; Whitworth, Phillip R. ; Matveev, Konstantin I. ( August 2021 , ASME Fluids Engineering Division Summer Meeting FEDSM2021)

   Hydrodynamic performance of ships can be greatly improved by the formation of air cavities under ship bottom with the purpose to decrease water friction on the hull surface. The air-cavity ships using this type of drag reduction are usually designed for and typically effective only in a relatively narrow range of speeds and hull attitudes and sufficient rates of air supply to the cavity. To investigate the behavior of a small-scale air-cavity boat operating under both favorable and detrimental loading and speed conditions, a remotely controlled model hull was equipped with a data acquisition system, video camera and onboard sensors to measure air-cavity characteristics, air supply rate and the boat speed, thrust and trim in operations on open-water reservoirs. These measurements were captured by a data logger and also wirelessly transmitted to a ground station and video monitor. The experimental air-cavity boat was tested in a range of speeds corresponding to length Froude numbers between 0.17 and 0.5 under three loading conditions, resulting in near zero trim and significant bow-up and bow-down trim angles at rest. Reduced cavity size and significantly increased drag occurred when operating at higher speeds, especially in the bow-up trim condition. The other objective of thismore »study was to determine whether computational fluid dynamics simulations can adequately capture the recorded behavior of the boat and air cavity. A computational software Star-CCM+ was utilized with the VOF method employed for multi-phase flow, RANS approach for turbulence modeling, and economical mesh settings with refinements in the cavity region and near free surface. Upon conducting the mesh verification study, several experimental conditions were simulated, and approximate agreement with measured test data was found. Adaptive mesh refinement and time step controls were also applied to compare results with those obtained on the user-generated mesh. Adaptive controls improved resolution of complex shedding patterns from the air cavity but had little impact on overall results. The presented here experimental approach and obtained results indicate that both outdoor experimentation and computationally inexpensive modeling can be used in the process of developing air-cavity systems for ship hulls.« less
2. Sensitivity Analysis of a Calibrated Data Center Model to Minimize the Site Survey Effort

   Singh, Saurabh ; Nemati, Kourosh ; Simon, Vibin ; Siddarth, Ashwin ; Seymour, Mark ; Agonafer, Dereje ( January 2021 , 2021 37th Semiconductor Thermal Measurement, Modeling & Management Symposium (SEMI-THERM))

   To reproduce a Digital Twin (DT) of a data center (DC), input data is required which is collected through site surveys. Data collection is an important step since accurate representation of a DC depends on capturing the necessary detail for various model fidelity levels of each DC component. However, guidance is lacking in this regard as to which components within the DC are crucial to achieve the level of accuracy desired for the computational model. And determining the input values of the component object parameters is an exercise in engineering judgement during site survey. Sensitivity analysis can be an effective methodology to determine how the level of simplification in component models can affect the model accuracy.In this study, a calibrated raised-floor DC model is used to study the sensitivity of a DC component's representation to the DC model accuracy. Commercial CFD tool, 6SigmaDC Room is used for modeling and simulation. A total of 8 DC components are considered and eventually ranked on the basis of time and effort required to collect model input data. For parametrized component object, the object's full range of input parameter values are considered, and simulations run. The results are compared with the baseline calibrated modelmore »to understand the trade-off between survey effort/cost and model accuracy. For the calibrated DC model and of the 8 components considered, it was observed that the chilled water piping branches, data cables and the cable penetration seal (found within cabinets) have considerable influence on the tile flow rate prediction accuracy.« less
3. Hierarchical off-diagonal low-rank approximation of Hessians in inverse problems, with application to ice sheet model initialization

   https://doi.org/10.1088/1361-6420/acd719  

   Hartland, Tucker ; Stadler, Georg ; Perego, Mauro ; Liegeois, Kim ; Petra, Noémi ( June 2023 , Inverse Problems)

   Abstract Obtaining lightweight and accurate approximations of discretized objective functional Hessians in inverse problems governed by partial differential equations (PDEs) is essential to make both deterministic and Bayesian statistical large-scale inverse problems computationally tractable. The cubic computational complexity of dense linear algebraic tasks, such as Cholesky factorization, that provide a means to sample Gaussian distributions and determine solutions of Newton linear systems is a computational bottleneck at large-scale. These tasks can be reduced to log-linear complexity by utilizing hierarchical off-diagonal low-rank (HODLR) matrix approximations. In this work, we show that a class of Hessians that arise from inverse problems governed by PDEs are well approximated by the HODLR matrix format. In particular, we study inverse problems governed by PDEs that model the instantaneous viscous flow of ice sheets. In these problems, we seek a spatially distributed basal sliding parameter field such that the flow predicted by the ice sheet model is consistent with ice sheet surface velocity observations. We demonstrate the use of HODLR Hessian approximation to efficiently sample the Laplace approximation of the posterior distribution with covariance further approximated by HODLR matrix compression. Computational studies are performed which illustrate ice sheet problem regimes for which the Gauss–Newton data-misfit Hessianmore »is more efficiently approximated by the HODLR matrix format than the low-rank (LR) format. We then demonstrate that HODLR approximations can be favorable, when compared to global LR approximations, for large-scale problems by studying the data-misfit Hessian associated with inverse problems governed by the first-order Stokes flow model on the Humboldt glacier and Greenland ice sheet.« less
4. A reaction mechanism for plasma electrolysis of AgNO ₃ forming silver nanoclusters and nanoparticles

   https://doi.org/10.1063/5.0127568  

   Raisanen, Astrid L. ; Mueller, Chelsea M. ; Chaudhuri, Subhajyoti ; Schatz, George C. ; Kushner, Mark J. ( November 2022 , Journal of Applied Physics)

   In plasma-driven solution electrolysis (PDSE), gas-phase plasma-produced species interact with an electrolytic solution to produce, for example, nanoparticles. An atmospheric pressure plasma jet (APPJ) directed onto a liquid solution containing a metallic salt will promote reduction of metallic ions in solution, generating metallic clusters that nucleate to form nanoparticles. In this article, results from a computational investigation are discussed of a PDSE process in which a radio-frequency APPJ sustained in helium impinges on a silver nitrate solution, resulting in growth of silver nanoparticles. A reaction mechanism was developed and implemented in a global plasma chemistry model to predict nanoparticle growth. To develop the reaction mechanism, density functional theory was used to generate probable silver growth pathways up to Ag 9 . Neutral clusters larger than Ag 9 were classified as nanoparticles. Kinetic reaction rate coefficients for thermodynamically favorable growth pathways were estimated based on an existing, empirically determined base reaction mechanism for smaller Ag particle interactions. These rates were used in conjunction with diffusion-controlled reaction rate coefficients that were calculated for other Ag species. The role of anions in reduction of Ag n ions in forming nanoparticles is also discussed. Oxygen containing impurities or admixtures to the helium, air entrainmentmore »into the APPJ, and dissociation of saturated water vapor above the solution can produce additional reactive oxygen species in solution, resulting in the production of anions and [Formula: see text] in particular. For a given molarity, delivering a sufficient fluence of reducing species will produce similar nanoparticle densities and sizes for all applied power levels. Comparisons are made to alternate models for nanoparticle formation, including charged nanoparticles and use of direct current plasmas.« less
5. GHub : Building a glaciology gateway to unify a community

   https://doi.org/10.1002/cpe.6130  

   Sperhac, Jeanette M. ; Poinar, Kristin ; Jones‐Ivey, Renette ; Briner, Jason ; Csatho, Beata ; Nowicki, Sophie ; Simon, Erika ; Larour, Eric ; Quinn, Justin ; Patra, Abani ( December 2020 , Concurrency and Computation: Practice and Experience)

   There is no consensus on how quickly the earth's ice sheets are melting due to global warming, nor on the ramifications to sea level rise. Due to its potential effects on coastal populations and global economies, sea level rise is a grave concern, making ice melt rates an important area of study. The ice‐sheet science community consists of two groups that perform related but distinct kinds of research: a data community, and a model building community. The data community characterizes past and current states of the ice sheets by assembling data from field and satellite observations. The modeling community forecasts the rate of ice‐sheet decline with computational models validated against observations. Although observational data and models depend on one another, these two groups are not well integrated. Better coordination between data collection efforts and modeling efforts is imperative if we are to improve our understanding of ice sheet loss rates. We present a new science gateway,GHub, a collaboration space for ice sheet scientists. This web‐accessible gateway will host datasets and modeling workflows, and provide access to codes that enable tool building by the ice sheet science community. Using GHub, we will collect and centralize existing datasets, creating data productsmore »that more completely catalog the ice sheets of Greenland and Antarctica. We will build workflows for model validation and uncertainty quantification, extending existing ice sheet models. Finally, we will host existing community codes, enabling scientists to build new tools utilizing them. With this new cyberinfrastructure, ice sheet scientists will gain integrated tools to quantify the rate and extent of sea level rise, benefitting human societies around the globe.

   « less