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Shallow paraboloidal shells of revolution are common components for reflectors, mirrors, etc. This study is to investigate the micro-control actions and distributed control effectiveness of precision paraboloidal shell structures laminated with segmented actuator patches.
A technique for the optimization of stability constrained geometrically nonlinear shallow trusses with snap through behavior is demonstrated using the arc length method and a strain energy density approach within a discrete finite element formulation. The optimization method uses an iterative scheme that evaluates the design variables' performance and then updates them according to a recursive formula controlled by the arc length method. A minimum weight design is achieved when a uniform nonlinear strain energy density is found in all members. This minimal condition places the design load just below the critical limit load causing snap through of the structure. The optimization scheme is programmed into a nonlinear finite element algorithm to find the large strain energy at critical limit loads. Examples of highly nonlinear trusses found in literature are presented to verify the method.
A comprehensive development of nondimensional parameters and equations for nonlinear and bifurcations analyses of quasi-shallow shells, based on the Donnell-Mushtari-Vlasov theory for thin anisotropic shells, is presented. A complete set of field equations for geometrically imperfect shells is presented in terms general of lines-of-curvature coordinates. A systematic nondimensionalization of these equations is developed, several new nondimensional parameters are defined, and a comprehensive stress-function formulation is presented that includes variational principles for equilibrium and compatibility. Bifurcation analysis is applied to the nondimensional nonlinear field equations and a comprehensive set of bifurcation equations are presented. An extensive collection of tables and figures are presented that show the effects of lamina material properties and stacking sequence on the nondimensional parameters.
The global hydrological cycle is central to the Earth's climate system, with rainfall and the physics of its formation acting as the key links in the cycle. Two-thirds of global rainfall occurs in the Tropics. Associated with this rainfall is a vast amount of heat, which is known as latent heat. It arises mainly due to the phase change of water vapor condensing into liquid droplets; three-fourths of the total heat energy available to the Earth's atmosphere comes from tropical rainfall. In addition, fresh water provided by tropical rainfall and its variability exerts a large impact upon the structure and motions of the upper ocean layer. Three-dimensional distributions of latent heating estimated from Tropical Rainfall Measuring Mission Precipitation Radar (TRMM PR)utilizing the Spectral Latent Heating (SLH) algorithm are analyzed. Mass-weighted and vertically integrated latent heating averaged over the tropical oceans is estimated as approx.72.6 J/s (approx.2.51 mm/day), and that over tropical land is approx.73.7 J/s (approx.2.55 mm/day), for 30degN-30degS. It is shown that non-drizzle precipitation over tropical and subtropical oceans consists of two dominant modes of rainfall systems, deep systems and congestus. A rough estimate of shallow mode contribution against the total heating is about 46.7 % for the average tropical oceans, which is substantially larger than 23.7 % over tropical land. While cumulus congestus heating linearly correlates with the SST, deep mode is dynamically bounded by large-scale subsidence. It is notable that substantial amount of rain, as large as 2.38 mm day-1 in average, is brought from congestus clouds under the large-scale subsiding circulation. It is also notable that even in the region with SST warmer than 28 oC, large-scale subsidence effectively suppresses the deep convection, remaining the heating by congestus clouds. Our results support that the entrainment of mid-to-lower-tropospheric dry air, which accompanies the large-scale subsidence is the major factor suppressing the deep convection. Therefore, representation of the realistic entrainment is very important for proper reproduction of precipitation distribution and resultant large-scale circulation.
The purpose of these experiments and analysis was to augment the heating database and tools used for assessment of impact-induced shallow-cavity damage to the thermal protection system of the Space Shuttle Orbiter. The effect of length and depth on the local heating disturbance of rectangular cavities tested at hypersonic freestream conditions has been globally assessed using the two-color phosphor thermography method. These rapid-response experiments were conducted in the Langley 31-Inch Mach 10 Tunnel and were initiated immediately prior to the launch of STS-114, the initial flight in the Space Shuttle Return-To-Flight Program, and continued during the first week of the mission. Previously-designed and numerically-characterized blunted-nose baseline flat plates were used as the test surfaces. Three-dimensional computational predictions of the entire model geometry were used as a check on the design process and the two-dimensional flow assumptions used for the data analysis. The experimental boundary layer state conditions were inferred using the measured heating distributions on a no-cavity test article. Two test plates were developed, each containing 4 equally-spaced spanwise-distributed cavities. The first test plate contained cavities with a constant length-to-depth ratio of 8 with design point depth-to-boundary-layer-thickness ratios of 0.1, 0.2, 0.35, and 0.5. The second test plate contained cavities with a constant design point depth-to-boundary-layer-thickness ratio of 0.35 with length-to-depth ratios of 8, 12, 16, and 20. Cavity design parameters and the test condition matrix were established using the computational predictions. Preliminary results indicate that the floor-averaged Bump Factor (local heating rate nondimensionalized by upstream reference) at the tested conditions is approximately 0.3 with a standard deviation of 0.04 for laminar-in/laminar-out conditions when the cavity length-to-boundary-layer thickness is between 2.5 and 10 and for cavities in the depth-to-boundary-layer-thickness range of 0.3 to 0.8. Over this same range of conditions and parameters, preliminary results also indicate that the maximum Bump Factor on the cavity centerline falls between 2.0 and 2.75, as long as the cavity-exit conditions remain laminar. Cavities with length-to-boundary-layer-thickness ratio less than 2.5 can not be easily classified with this approach and require further analysis.
Floor-fractured craters (FFCs) are a class of lunar craters defined by their distinctly shallow, often plate-like floors, and combinations of radial, con-centric, and polygonal floor-fractures; a variety of other interior features are often observed, such as moats, ridges, small dark-haloed pits, and patches of mare material. They were first classified by Schultz [1] , who recognized eight overall types of floor-fractured crater. These eight subtypes have widely differing appearances, a factor that could provide insight into formation mechanisms (different manifestations of the same mechanism, or indicators of varying formation mechanisms). Two formation mechanisms for FFCs were initially proposed: 1) magmatic intrusion [1], in which magma rising toward the surface in dikes encountered low-density breccia lenses beneath crater floors and spread laterally to form sills, raising and fracturing the crater floor. 2) viscous relaxation [2], in which the properties of the crust permitted viscous flow in the vicinity of the crater, causing long-wavelength relaxation of the topography and uplift and fracturing of the crater floor. Critical to distinguishing between these two end-member hypotheses and identifying others is a quantitative assessment of the topography of FFCs and knowledge of their regional and local settings. The purpose of this study is to use newly available Lunar Reconnaissance Orbiter (LRO) Lunar Orbiter Laser Altimeter (LOLA) altimeter and Lunar Reconnaissance Orbiter Camera (LROC) image data to provide an updated global catalog of the locations, classes, morphometric and morphologic characteristics of all lunar floor-fractured craters. We use the excellent 8-class system initially described in Schultz [1] as a starting point for classification and the enhanced LOLA/LROC data sets to examine and categorize all FFCs; we found evidence for a new FFC class, discernably different from the previously existing types. Our approach, and the global categorization of all FFCs, permits the spatial distribution of each FFC-subtype to be plotted and assessed allowing for further investigation into FFC formation mechanisms. Upon completion, the data set will be made available on our web site at http://www.planetary.brown.edu/html_pages/data.htm.
Laboratory experimental evidence using Raman spectroscopy has shown that liquid brine may form below the shallow subsurface of Mars. A simpler experimental method to verify the presence of liquid brine or liquid water below Mars surface is needed. In this paper, a ring resonator is used to detect the phase change between frozen water and liquid water below a sandy soil that simulates the Mars surface. Experimental data shows that the ring resonator can detect the melting of thin layers of frozen brine or water up to 15 mm below the surface.
Laboratory experimental evidence using Raman spectroscopy has shown that liquid brine may form below the shallow subsurface of Mars. A simpler experimental method to verify the presence of liquid brine or liquid water below Mars surface is needed. In this paper, a ring resonator is used to detect the phase change between frozen water and liquid water below a sandy soil that simulates the Mars surface. Experimental data shows that the ring resonator can detect the melting of thin layers of frozen brine or water up to 15 mm below the surface.
Weather and climate models have long struggled to realistically simulate the Madden-Julian Oscillation (MJO). Here we present a significant improvement in MJO simulation in NASA's GEOS atmospheric model with the implementation of 2-moment microphysics and the UW shallow cumulus parameterization. Comparing ten-year runs (2007-2016) with the old (1mom) and updated (2mom+shlw) model physics, the updated model has increased intra-seasonal variance with increased coherence. Surface fluxes and OLR are found to vary more realistically with precipitation, and a moisture budget suggests that changes in rain reevaporation and the cloud longwave feedback help support heavy precipitation. Preliminary results also show improved MJO hindcast skill.
Using Viking Orbiter images, detailed photoclinometric profiles were obtained across irregular depressions, fretted fractures, troughs and pits, solitary scarps, and simple grabens in the north Tharsis region of Mars. This data allows inferences to be made on the shallow crustal structure of this region. Topographical data obtained for Mars is discussed in relation to mechanical discontinuities.
The widely used Moderate Resolution Imaging Spectroradiometer (MODIS) Dark-Target (DT) aerosol product fails to accurately retrieve Aerosol Optical Depth (AOD) over shallow and turbid Coastal Waters (CWs). To fill in gaps, and to improve land to ocean AOD continuity, we developed a coastal water retrieval algorithm at a spatial resolution of 1 km (CW-1km). CW-1km relies on observed top-of-atmosphere reflectance at 2.1 μm (ρ2.1), both to derive AOD and to perform a spatial variation test that enhances the existing DT masks for clouds and land. We show that the CW-1km improves spatial continuity of AOD between land, coast, and open ocean, while also increasing AOD product availability by 47.0%. Comparing with 15 years of marine aerosol network measurements, CW-1km AODs are validated to have a normalized mean bias of 1.0%, which is much smaller than 17.6% for the original DT product.
In neutrino interactions with nucleons and nuclei, Shallow Inelastic Scattering (SIS) refers to processes, dominated by non-resonant contributions, in the kinematic region where $Q^2$ is small and the invariant mass of the hadronic system, $W$, is above the pion production threshold. The extremely rich science of this complex region, poorly understood both theoretically and experimentally, encompasses the transition from interactions described in terms of hadronic degrees of freedom to interactions with quarks and gluons described by perturbative QCD. Since a large fraction of events in NOvA and DUNE, and in atmospheric neutrino measurements such as IceCube-Upgrade, KM3NeT, Super- and Hyper-Kamiokande, are from this SIS region, there is a definite need to improve our knowledge of this physics. This LoI summarizes the current understandings of the SIS physics and a series of proposals for the path to forward.
Geothermal heat pump (GHP), which is also referred as ground source heat pump, is the most energy-efficient technology for space heating and cooling. However, the application of GHP is hindered by its high initial cost, of which approximately 30% is for the ground heat exchanger (GHE). In recent years, researchers have developed different types of shallow bore ground heat exchangers (SBGHE) intending to reduce the cost of drilling. The ability to predict the thermal response of an SBGHE is critical for sizing SBGHE. While g-functions have been commonly used for predicting the thermal response of conventional vertical bore ground heat exchangers (VBGHE), they cannot be directly used for predicting the performance of SBGHE because they did not account for the impacts of the seasonal variation of the soil temperature along with the depth of an SBGHE. In addition, an SBGHE has a larger thermal mass within the borehole than the VBGHE due to the larger borehole diameter of SBGHE. This study develops new g-function data pairs for a new design of SBGHE, which is named Underground Thermal Battery (UTB). Impacts of the seasonal variation of soil temperature on the thermal response of UTB were accounted for by superposing a time-dependent soil temperature onto the g-functions calculated with a numerical model that assumes constant undisturbed soil temperature. The TOUGH program was used to predict the thermal response of several configurations involving multiple UTBs. The results indicate that the proposed methodology is appropriate to generate g-functions for the UTB, and the g-function value of UTB is much lower than that of VBGHE in the time range of 15 min to 1 year due to the large thermal mass and convection heat transfer within the UTB.
Geological thermal energy storage (GeoTES) utilizes the underground reservoirs to storage and dispatch energy per given demand schedule over a time scale up to seasons of a year. The energy input can be of various sources/forms; in this paper, we investigate 1) the GeoTES technology with solar thermal hybridization and using depleted oil/gas reservoirs; 2) the GeoTES technology with heat pumps charged by excess renewable electricity and using low-temperature shallow reservoirs. For each GeoTES technology, we carry out the suitability analysis of candidate reservoirs, develop initial techno-economic models, and validate the model with selected case study. The paper provides an overview of our technical progress on the topics of concern and aims to promote a wider acceptance of the GeoTES technologies in the future energy market.
When trying to fit a deep neural network (DNN) to a G-invariant target function with G a group, it only makes sense to constrain the DNN to be G-invariant as well. However, there can be many different ways to do this, thus raising the problem of “G-invariant neural architecture design”: What is the optimal Ginvariant architecture for a given problem? Before we can consider the optimization problem itself, we must understand the search space, the architectures in it, and how they relate to one another. In this paper, we take a first step towards this goal; we prove a theorem that gives a classification of all G-invariant single-hidden-layer or “shallow” neural network (G-SNN) architectures with ReLU activation for any finite orthogonal group G, and we prove a second theorem that characterizes the inclusion maps or “network morphisms” between the architectures that can be leveraged during neural architecture search (NAS). The proof is based on a correspondence of every G-SNN to a signed permutation representation of G acting on the hidden neurons; the classification is equivalently given in terms of the first cohomology classes of G, thus admitting a topological interpretation. The G-SNN architectures corresponding to nontrivial cohomology classes have, to our knowledge, never been explicitly identified in the literature previously. Using a code implementation, we enumerate the G-SNN architectures for some example groups G and visualize their structure. Lastly, we prove that architectures corresponding to inequivalent cohomology classes coincide in function space only when their weight matrices are zero, and we discuss the implications of this for NAS.
Scientists at Berkeley Lab have teamed up with The University of Hawai‘i at Manoa (UH Manoa) through the U.S. Department of Energy’s (DOE’s) Energy Transitions Initiative Partnership Project (ETIPP) to evaluate the technological and market feasibility of shallow geothermal heat exchanger (GHE) technology for building cooling, energy efficiency, and emissions reduction applications in Hawai’i. The team is assessing the data necessary to model the feasibility of deploying this technology, the actual models that will be used, and what hurdles need to be overcome to install a demonstration case. UH has an abundance of geologic and geothermal data and is looking to the national labs’ expertise to execute this analysis. UH is also interested in investigating policy, regulatory, and business conditions advantageous for implementation of a pilot project, and more broad deployment of this technology in Hawai‘i. In many locations around the world, the demands for heating and cooling are roughly balanced over the course of the year, so GHEs do not cause significant long-term changes in subsurface temperature. This is not the case in Hawai’i, where the demand for heating is very small, meaning that over time, GHEs will add heat to the subsurface. If temperatures increase significantly, GHE systems will not work as designed. Regional groundwater flow has the potential to sweep heated water away from boreholes, thereby maintaining the functionality of the GHE system. Significant regional groundwater flow requires two things: a sufficiently large driving hydraulic head gradient (usually closely related to surface topography), and sufficient porosity and permeability to enable groundwater to flow in large enough quantities to enable near-borehole temperatures to be maintained at ambient values. Hawai‘i’s volcanic terrain offers ample surface topographic variation. The lava itself shows an extremely large range of porosity and permeability, making it crucial to select sites with large enough values of these properties. Numerical modeling of coupled groundwater and heat flow can be used to determine how large is large enough. Both closed-loop and open-loop systems are being investigated. Another option being considered is using cool seawater as the source of chill. Currently work is progressing on two fronts. A hydrogeologic model for a closed-loop system is being developed for the Stan Sheriff Center at the UH Manoa campus, where a subsurface karst system immediately downgradient of the borefield may provide efficient removal of heated groundwater. The team will also develop a technoeconomic model for this site to compare the cost of cooling using a GHE system with the costs of operating the current air conditioning system. At the state scale, geographic information system (GIS) layers of various attributes relevant for GHE are being combined to develop an overall favorability map for employing GHE in Hawai‘i.
Cross section measurements are essential for all neutrino oscillation experiments. In fact, uncertaintiesassociated to cross section model parameters constitute one of the dominant sources oferrors in current oscillation analyses. In particular, understanding neutrino-induced pion productionin the kinematic regime known as shallow inelastic scattering (SIS) is critical for improvingneutrino interaction modeling in event generators. In this study, 416,233 (237,468) muon neutrino(antineutrino) interactions are measured in a SIS background region, predominantly made ofbaryon resonances. The analyzed datasets were collected from 2013 to 2019, comprising neutrinosgenerated by the Fermilab NuMI facility, with mean energy of 6 GeV, and the interactions occurredon the MINERvA hydrocarbon target. The measurements are presented as double-differential crosssections in terms of the outgoing muon longitudinal and transverse momentum components, aswell as the Bjorken x and y variables. Comparisons between the extracted data and predictionsfrom several generators reveal significant discrepancies across most kinematic bins.
For tidal-stream energy to become a competitive renewable energy source, clustering multiple turbines into arrays is paramount. Array optimisation is thus critical for achieving maximum power performance and reducing cost of energy. However, ascertaining an optimal array layout is a complex problem, subject to specific site hydrodynamics and multiple inter-disciplinary constraints. In this work, we present a novel optimisation approach that combines an analytical-based wake model, FLORIS, with an ocean model, Thetis. The approach is demonstrated through applications of increasing complexity. By utilising the method of analytical wake superposition, the addition or alteration of turbine position does not require re-calculation of the entire flow field, thus allowing the use of simple heuristic techniques to perform optimisation at a fraction of the computational cost of more sophisticated methods. Using a custom condition-based placement algorithm, this methodology is applied to the Pentland Firth for arrays with turbines of 3.05 m/s rated speed, demonstrating practical implications whilst considering the temporal variability of the tide. For a 24-turbine array case, micro-siting using this technique delivered an array 15.8% more productive on average than a staggered layout, despite flow speeds regularly exceeding the rated value. Performance was evaluated through assessment of the optimised layout within the ocean model that treats turbines through a discrete turbine representation. Used iteratively, this methodology could deliver improved array configurations in a manner that accounts for local hydrodynamic effects.