SURF Reactive Burn Model Validation - A preliminary assessment of the SURF implementation in the FLAG hydrocode
This report describes the SURF reactive burn model and its use cases.
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This report describes the SURF reactive burn model and its use cases.
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The NASA Innovative Advanced Concept (NIAC) program has been funding work at KSC on a novel coating that should allow a future spacecraft to come close to the Sun. The NIAC Symposium will be the last week of September and it is a requirement that the funded material be presented both orally and at a poster session. This DAA submission is requesting approval to go public with both the presentation and the poster.
High-resolution urban climate modeling has faced substantial challenges due to the absence of a globally consistent, spatially continuous, and accurate dataset to represent the spatial heterogeneity of urban surfaces and their biophysical properties. This deficiency has long obstructed the development of urban-resolving Earth system models (ESMs) and ultra-high-resolution urban climate modeling, over large domains. Here, we present U-Surf, a first-of-its-kind 1 km resolution present-day (circa 2020) global continuous urban surface parameter dataset. Using the urban canopy model (UCM) in the Community Earth System Model as a base model for satisfying dataset requirements, U-Surf leverages the latest advances in remote sensing, machine learning, and cloud computing to provide the most relevant urban surface biophysical parameters, including radiative, morphological, and thermal properties, for UCMs at the facet and canopy level. Generated using a systematically unified workflow, U-Surf ensures internal consistency among key parameters, making it the first globally coherent urban canopy surface dataset. U-Surf significantly improves the representation of the urban land heterogeneity both within and across cities globally; provides essential, high-fidelity surface biophysical constraints to urban-resolving ESMs; enables detailed city-to-city comparisons across the globe; and supports next-generation kilometer-resolution Earth system modeling across scales. U-Surf parameters can be easily converted or adapted to various types of UCMs, such as those embedded in weather and regional climate models, as well as air quality models. The fundamental urban surface constraints provided by U-Surf can also be used as features for machine learning models and can have other broad-scale applications for socioeconomic, public health, and urban planning contexts. We expect U-Surf to advance the research frontier of urban system science, climate-sensitive urban design, and coupled human–Earth systems in the future. The dataset is publicly available at https://doi.org/10.5281/zenodo.11247598 (Cheng et al., 2024).
The coupling of ecology and evolution during range expansions enables mutations to establish at expanding range margins and reach high frequencies. This phenomenon, called allele surfing, is thought to have caused revolutions in the gene pool of many species, most evidently in microbial communities. It has remained unclear, however, under which conditions allele surfing promotes or hinders adaptation. Here in this paper, using microbial experiments and simulations, we show that, starting with standing adaptive variation, range expansions generate a larger increase in mean fitness than spatially uniform population expansions. The adaptation gain results from ‘soft’ selective sweeps emerging from surfing beneficial mutations. The rate of these surfing events is shown to sensitively depend on the strength of genetic drift, which varies among strains and environmental conditions. More generally, allele surfing promotes the rate of adaptation per biomass produced, which could help developing biofilms and other resource-limited populations to cope with environmental challenges.
A unique collection of computer codes, Space Debris Surfaces (SD_SURF), have been developed to assist in the design and analysis of space debris protection systems. SD_SURF calculates and summarizes a vehicle's vulnerability to space debris as a function of impact velocity and obliquity. An SD_SURF analysis will show which velocities and obliquities are the most probable to cause a penetration. This determination can help the analyst select a shield design which is best suited to the predominant penetration mechanism. The analysis also indicates the most suitable parameters for development or verification testing. The SD_SURF programs offer the option of either FORTRAN programs and Microsoft EXCEL spreadsheets and macros. The FORTRAN programs work with BUMPERII version 1.2a or 1.3 (Cosmic released). The EXCEL spreadsheets and macros can be used independently or with selected output from the SD_SURF FORTRAN programs.
The National Aeronautics and Space Administration (NASA) Armstrong Flight Research Center completed a series of research flights to better understand the challenges of aircraft wake surfing using civilian airplanes and commercial avionics. Airlines and air cargo carriers have identified uncertainty about increased passenger/crew discomfort due to noise and vibrations as a potential obstacle to the widespread adoption of aircraft wake surfing. To measure the effects of wake surfing on passenger ride quality, NASA instrumented a business jet with cabin noise and vibration sensors. The airplane was then flown under control of an experimental autopilot at multiple locations within the wake of a similar airplane. This paper presents a summary of the measurements collected on those flights, an assessment of passenger discomfort correlated with wake surfing performance benefits, and qualitative evaluations collected from passengers aboard during the research flights.
The Enhanced Traffic Situational Awareness on the Airport Surface with Indications and Alerts (SURF IA) algorithm was evaluated in a fast-time batch simulation study at the National Aeronautics and Space Administration (NASA) Langley Research Center. SURF IA is designed to increase flight crew situation awareness of the runway environment and facilitate an appropriate and timely response to potential conflict situations. The purpose of the study was to evaluate the performance of the SURF IA algorithm under various runway scenarios, multiple levels of conflict detection and resolution (CD&R) system equipage, and various levels of horizontal position accuracy. This paper gives an overview of the SURF IA concept, simulation study, and results. Runway incursions are a serious aviation safety hazard. As such, the FAA is committed to reducing the severity, number, and rate of runway incursions by implementing a combination of guidance, education, outreach, training, technology, infrastructure, and risk identification and mitigation initiatives [1]. Progress has been made in reducing the number of serious incursions - from a high of 67 in Fiscal Year (FY) 2000 to 6 in FY2010. However, the rate of all incursions has risen steadily over recent years - from a rate of 12.3 incursions per million operations in FY2005 to a rate of 18.9 incursions per million operations in FY2010 [1, 2]. The National Transportation Safety Board (NTSB) also considers runway incursions to be a serious aviation safety hazard, listing runway incursion prevention as one of their most wanted transportation safety improvements [3]. The NTSB recommends that immediate warning of probable collisions/incursions be given directly to flight crews in the cockpit [4].
PBX 9501 is a plastic bonded explosive composed of 95 wt % HMX and a binder; see [Gibbs and Popolato, 1980, pp. 109–119]. SURF is a reactive burn model for shock initiation and propagation of detonation waves. It has previously been calibrated for PBX 9501. Here the SURF model is recalibrated for PBX 9501; specifically, lot 730-010 at ρ = 1.837 g/cc 3 . The new calibration uses the Davis reactants and products EOS calibrated for the AWSD model [Aslam et al., 2020]. The burn rate in the shock initiation regime is fit to the Pop plot from 5 embedded gauge shock-to-detonation transition (SDT) experiments from [Gustavsen et al., 1999, see fig 12 and table 5]. In the propagation regime, the burn rate is fit to curvature effect data (detonation speed as function of front curvature); see [Aslam, 2007]. Also the burn parameters are adjusted to fit the gap-stick experiment [Hill et al., 2018]. Simulating the detonation wave speed in this experiment requires a model that is accurate for initiation with complex shock loading; in particular, a pressure decreasing gradient behind a curved lead shock. This is more difficult than calibrating to the standard SDT experiments which are 1-D and driven by a sustained shock. Simulations of the gap-stick experiment for PBX 9501 with the SURF model will be discussed in a subsequent report.
The former Homestake gold mine in Lead, South Dakota is being transformed into a dedicated laboratory to pursue underground research in rare-process physics, as well as offering research opportunities in other disciplines. A key component of the Sanford Underground Research Facility (SURF) is the Davis Campus, which is in operation at the 4850-foot level (4300 m.w.e) and currently hosts three projects: the LUX dark matter experiment, the Majorana Demonstrator neutrinoless double-beta decay experiment and the Berkeley and CUBED low-background counters. Plans for possible future experiments at SURF are well underway and include long baseline neutrino oscillation experiments, future dark matter experiments as well as nuclear astrophysics accelerators. Facility upgrades to accommodate some of these future projects have already started. SURF is a dedicated facility with significant expansion capability. These plans include a Generation-2 Dark Matter experiment and the US flagship neutrino experiment, LBNE.
In this paper, we introduce Surf-Deformer, a code deformation framework that seamlessly integrates adaptive defect mitigation functionality into the current surface code workflow. It crafts several basic deformation instructions based on fundamental gauge transformations, which can be combined to explore a larger design space than previous methods. This enables more optimized deformation processes tailored to specific defect situations, restoring the QEC capability of deformed codes more efficiently with minimal qubit resources. Additionally, we design an adaptive code layout that accommodates our defect mitigation strategy while ensuring efficient execution of logical operations. Our evaluation shows that Surf-Deformer outperforms previous methods by significantly reducing the end-to-end failure rate of various quantum programs by 35× to 70×, while requiring only about 50% of the qubit resources compared to the previous method to achieve the same level of failure rate. Ablation studies show that Surf-Deformer surpasses previous defect removal methods in preserving QEC capability and facilitates surface code communication by achieving nearly optimal throughput.
As a part of the U.S. Department of Energy (DOE) SubTER (Subsurface Technology and Engineering Research, Development and Demonstration) initiative, University of Wisconsin- Madison, Sandia National Laboratories, and Lawrence Berkeley National Laboratory conducted the Permeability (k) and Induced Seismicity Management for Energy Technologies (kISMET) project. The objectives of the project are to define the in situ status of stress in the Sanford Underground Research Facility (SURF) in Lead, South Dakota and to establish the relations between in situ stress and induced fracture through hydraulically stimulating the fracture. (SURF) in Lead, South Dakota. In situ tests are conducted in a 7.6 cm diameter and 100 long vertical borehole located in the 4850 Level West Access Drift near Davies Campus of SURF (Figure 1). The borehole is located in the zone of Precambrian Metamorphic Schist.
Developed by Menikoff and Shaw, the SURF reactive burn model builds on the Ignition and Growth concept by incorporating the lead shock pressure directly into the volumetric hot-spot burn rate. The plus-extension augments the model with a late time surface burn rate due to carbon clustering. Together, SURF and SURFplus allow for robust modeling of both conventional and insensitive high explosives. Practically, the SURF burn models require shock detection and the advection of the lead shock pressure as an additional material field. Calibrated parameters for given equations of state and thermodynamic closure are dependent on initial temperature and density. An implementation in Python is given.
The age of the surf clam (Spisula solidissima) can be determined with the use of the Digital Image Processor. This technique is used in conjunction with a modified method for aging, refined by John Ropes of the Woods Hole Laboratory, Massachusetts. This method utilizes a thinned sectioned chondrophore of the surf clam which contains annual rings. The rings of the chondrophore are then counted to determine age. By digitizing the chondrophore, the Digital Image Processor is clearly able to separate these annual rings more accurately. This technique produces an easier and more efficient way to count annual rings to determine the age of the surf clam.
As a verification test of the SURF and SURFplus models in the xRage code we use a propagating underdriven detonation wave in 1-D. This is about the only test cases for which an accurate solution can be determined based on the theoretical structure of the solution. The solution consists of a steady ZND reaction zone profile joined with a scale invariant rarefaction or Taylor wave and followed by a constant state. The end of the reaction profile and the head of the rarefaction coincide with the sonic CJ state of the detonation wave. The constant state is required to match a rigid wall boundary condition. For a test case, we use PBX 9502 with the same EOS and burn rate as previously used to test the shock detector algorithm utilized by the SURF model. The detonation wave is propagated for 10 μs (slightly under 80mm). As expected, the pointwise errors are largest in the neighborhood of discontinuities; pressure discontinuity at the lead shock front and pressure derivative discontinuities at the head and tail of the rarefaction. As a quantitative measure of the overall accuracy, the L2 norm of the difference of the numerical pressure and the exact solution is used. Results are presented for simulations using both a uniform grid and an adaptive grid that refines the reaction zone.
The previous study used an underdriven detonation wave (steady ZND reaction zone profile followed by a scale invariant rarefaction wave) for PBX 9502 as a validation test of the implementation of the SURF and SURFplus models in the xRage code. Even with a fairly fine uniform mesh (12,800 cells for 100mm) the detonation wave profile had limited resolution due to the thin reaction zone width (0.18mm) for the fast SURF burn rate. Here we study the effect of finer resolution by comparing results of simulations with cell sizes of 8, 2 and 1 μm, which corresponds to 25, 100 and 200 points within the reaction zone. With finer resolution the lead shock pressure is closer to the von Neumann spike pressure, and there is less noise in the rarefaction wave due to fluctuations within the reaction zone. As a result the average error decreases. The pointwise error is still dominated by the smearing the pressure kink in the vicinity of the sonic point which occurs at the end of the reaction zone.
The previous studies used an underdriven detonation wave in 1-dimension (steady ZND reaction zone profile followed by a scale-invariant rarefaction wave) for PBX 9502 as a verification test of the implementation of the SURF and SURFplus models in the xRage code. Since the SURF rate is a function of the lead shock pressure, the question arises as to the effect on accuracy of variations in the detected shock pressure due to the alignment of the shock front with the mesh. To study the effect of mesh alignment we simulate a cylindrically diverging detonation wave using a planar 2-D mesh. The leading issue is the magnitude of azimuthal asymmetries in the numerical solution. The 2-D test case does not have an exact analytic solution. To quantify the accuracy, the 2-D solution along rays through the origin are compared to a highly resolved 1-D simulation in cylindrical geometry.