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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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From Quanta to the Continuum: Opportunities for Mesoscale Science
This report explores the opportunity and defines the research agenda for mesoscale science—discovering, understanding, and controlling interactions among disparate systems and phenomena to reach the full potential of materials complexity and functionality. The ability to predict and control mesoscale phenomena and architectures is essential if atomic and molecular knowledge is to blossom into a next generation of technology opportunities, societal benefits, and scientific advances.. The body of this report outlines the need, the opportunities, the challenges, and the benefits of mastering mesoscale science.
Science and Technology Review April/May 2015
Abstract not provided
DEM Particle Fracture Model
An adaptive particle fracture model in poly-ellipsoidal Discrete Element Method is developed. The poly-ellipsoidal particle will break into several sub-poly-ellipsoids by Hoek-Brown fracture criterion based on continuum stress and the maximum tensile stress in contacts. Also Weibull theory is introduced to consider the statistics and size effects on particle strength. Finally, high strain-rate split Hopkinson pressure bar experiment of silica sand is simulated using this newly developed model. Comparisons with experiments show that our particle fracture model can capture the mechanical behavior of this experiment very well, both in stress-strain response and particle size redistribution. The effects of density and packings o the samples are also studied in numerical examples.
McCallen Professional Research and Teaching Leave Report
This end of assignment report for a Professional Research and Teaching (PRT) Leave award includes the attached assessment of success by the host organization, University of California Davis (UCD). The following summarizes the accomplishments and attached are a selection of documented items.
On Artificial Viscosity for Shocks in Porous Materials
The treatment of downstream oscillations in shockwave simulations on discrete grids dates back to the 1940’s with the introduction of an artificial viscosity. These additional term(s) have been successful at suppressing or eliminating oscillations in smooth, well-defined equations of state. This report identifies a shortcoming of several solution methodologies and viscosity formulations that are easily observed when solid equations of state are modified with compaction models or run with a significantly lower density (i.e. ρ < ρ 0 ). The obvious solution is to increase parameter values for the artificial viscosity, but this could lead to deleterious effects in multi-material problems if the viscosity is globally set.
2015 LLNL Nuclear Forensics Summer Program
The Lawrence Livermore National Laboratory (LLNL) Nuclear Forensics Summer Program is designed to give graduate students an opportunity to come to LLNL for 8–10 weeks for a hands-on research experience. Students conduct research under the supervision of a staff scientist, attend a weekly lecture series, interact with other students, and present their work in poster format at the end of the program. Students also have the opportunity to meet staff scientists one-on-one, participate in LLNL facility tours (e.g., the National Ignition Facility and Center for Accelerator Mass Spectrometry) to gain a better understanding of the multidisciplinary, on going science at LLNL. Currently called the Nuclear Forensics Summer Program, this program began 15 years ago as the Actinide Sciences Summer Program. The program is run within the Glenn T. Seaborg Institute in the Physical and Life Sciences Directorate at LLNL. The goal of the Nuclear Forensics Summer Program is to facilitate the training of the next generation of nuclear scientists and engineers to solve critical national security problems in the field of nuclear forensics and have the students participate in conducting research at LLNL. We select students who are majoring in physics, chemistry, geology, mathematics, nuclear engineering, chemical engineering and environmental sciences. Students engage in research projects in the disciplines of actinide chemistry, radiochemistry, isotopic analysis, computational analysis, radiation detection, and nuclear engineering in order to strengthen the “pipeline” for future scientific disciplines critical to DHS (DNDO), NNSA.
Spacecraft Geometry Effects on Kinetic Impactor Missions
Abstract The DART (Double Asteroid Redirection Test) mission will impact a spacecraft on the secondary (Dimorphos) of the binary asteroid system Didymos in 2022 September, with the goal of altering the orbital period of Dimorphos about Didymos sufficiently to be observed from ground-based observations. Numerical impact modeling is a crucial component in understanding the outcome of the DART experiment, and while many have investigated the effects of target properties, such as material strength and porosity (which remain unknown), an often overlooked factor is the importance of accurately representing the spacecraft itself in such models. Most impact modeling to date has considered simple impactor geometries such as a solid uniform sphere, but in reality the spacecraft is a complex shape full of different components, open spaces, and thin walled structures. At a minimum, a simple solid representation underestimates the surface area of the impact: for a small body such as Dimorphos (approximately 160 m in diameter), the difference between a spacecraft spanning 20 m (including solar arrays) impacting and a sub-1 m idealized shape may be important. In this paper, we compare models impacting high-fidelity models of the spacecraft based on the CAD geometry with various simplified impactors, in order to assess the potential importance of this effect. We find that the difference between the simplest impactor geometries (such as a uniform sphere) and the real spacecraft is measurable, and has an interesting dependence on the material properties of the asteroid itself.
Electronics for Large Superconducting Tunnel Junction Detector Arrays for Synchrotron Soft X-ray Research (Final Report)
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NON-DISPERSIVE RESPONSE OF A HOPKINSON BAR TO SHOCK LOADING
Abstract not provided
Method of thin film adhesion pretreatment
A circuit board comprising a substrate and a circuit trace. The substrate includes a surface etched via ion milling over a circuit area such that the surface has an increased roughness. The circuit trace forms portions of an electronic circuit and may be created from a thin conductive film deposited on the surface within the circuit area. The circuit trace adheres more strongly to the roughened substrate surface, which prevents the circuit trace from peeling or becoming delaminated from the substrate surface.
What is Data-Intensive Science?
What is Data Intensive Science? Today we are living in a digital world, where scientists often no longer interact directly with the physical object of their research, but do so via digitally captured, reduced, calibrated, analyzed, synthesized and, at times, visualized data. Advances in experimental and computational technologies have lead to an exponential growth in the volumes, variety and complexity of this data and while the deluge is not happening everywhere in an absolute sense, it is in a relative one. Science today is data intensive. Data intensive science has the potential to transform not only how we do science, but how quickly we can translate scientific progress into complete solutions, policies, decisions and ultimately economic success. Critically, data intensive science touches some of the most important challenges we are facing. Consider a few of the grand challenges outlined by the U.S. National Academy of Engineering: make solar energy economical, provide energy from fusion, develop carbon sequestration methods, advance health informatics, engineer better medicines, secure cyberspace, and engineer the tools of scientific discovery. Arguably, meeting any of these challenges requires the collaborative effort of trans-disciplinary teams, but also significant contributions from enabling data intensive technologies. Indeed for many of them, advances in data intensive research will be the single most important factor in developing successful and timely solutions. Simple extrapolations of how we currently interact with and utilize data and knowledge are not sufficient to meet this need. Given the importance of these challenges, a new, bold vision for the role of data in science, and indeed how research will be conducted in a data intensive environment is evolving.
Streamlining the Design Tradespace for Earth Imaging Constellations
Distributed Spacecraft Missions (DSMs) are gaining momentum in their application to Earth Observation (EO) missions owing to their unique ability to increase observation sampling in spatial, spectral, angular and temporal dimensions simultaneously. DSM design includes a much larger number of variables than its monolithic counterpart, therefore, Model-Based Systems Engineering (MBSE) has been often used for preliminary mission concept designs, to understand the trade-offs and interdependencies among the variables. MBSE models are complex because the various objectives a DSM is expected to achieve are almost always conflicting, non-linear and rarely analytical. NASA Goddard Space Flight Center is developing a pre-Phase A tool called "Trade-space Analysis Tool for Constellations" (TAT-C) to initiate constellation mission design. The tool will allow users to explore the tradespace between various performance, cost and risk metrics (as a function of their science mission) and select Pareto optimal architectures that meet their requirements. This paper focuses on the tradespace search and how it can be streamlined by combining physical rules, as well as well-designed orbit and coverage computations, thus yielding significant speed-ups. Two use cases are shown as representative examples of the utility of TAT-C generated trades, and results are preliminarily validated against AGI's Systems Tool Kit.
SU-E-T-455: Impact of Different Independent Dose Verification Software Programs for Secondary Check
Purpose: There have been many reports for different dose calculation algorithms for treatment planning system (TPS). Independent dose verification program (IndpPro) is essential to verify clinical plans from the TPS. However, the accuracy of different independent dose verification programs was not evident. We conducted a multi-institutional study to reveal the impact of different IndpPros using different TPSs. Methods: Three institutes participated in this study. They used two different IndpPros (RADCALC and Simple MU Analysis (SMU), which implemented the Clarkson algorithm. RADCALC needed the input of radiological path length (RPL) computed by the TPSs (Eclipse or Pinnacle3). SMU used CT images to compute the RPL independently from TPS). An ion-chamber measurement in water-equivalent phantom was performed to evaluate the accuracy of two IndpPros and the TPS in each institute. Next, the accuracy of dose calculation using the two IndpPros compared to TPS was assessed in clinical plan. Results: The accuracy of IndpPros and the TPSs in the homogenous phantom was +/−1% variation to the measurement. 1543 treatment fields were collected from the patients treated in the institutes. The RADCALC showed better accuracy (0.9 ± 2.2 %) than the SMU (1.7 ± 2.1 %). However, the accuracy was dependent on the TPS (Eclipse: 0.5%, Pinnacle3: 1.0%). The accuracy of RADCALC with Eclipse was similar to that of SMU in one of the institute. Conclusion: Depending on independent dose verification program, the accuracy shows systematic dose accuracy variation even though the measurement comparison showed a similar variation. The variation was affected by radiological path length calculation. IndpPro with Pinnacle3 has different variation because Pinnacle3 computed the RPL using physical density. Eclipse and SMU uses electron density, though.
Vacancies in graphene: an application of adiabatic quantum optimization
Quantum annealers have grown in complexity to the point that quantum computations involving a few thousand qubits are now possible. In this paper, with the intentions to show the feasibility of quantum annealing to tackle problems of physical relevance, we used a simple model, compatible with the capability of current quantum annealers, to study the relative stability of graphene vacancy defects. By mapping the crucial interactions that dominate carbon-vacancy interchange onto a quadratic unconstrained binary optimization problem, our approach exploits the ground state as well as the excited states found by the quantum annealer to extract all the possible arrangements of multiple defects on the graphene sheet together with their relative formation energies. Furthermore, this approach reproduces known results and provides a stepping stone towards applications of quantum annealing to problems of physical–chemical interest.
Implementing contact angle boundary conditions for second-order Phase-Field models of wall-bounded multiphase flows
In the present work, a general formulation is proposed to implement the contact angle boundary conditions for the second-order Phase-Field models, which is applicable to N-phase (N ≥ 2) moving contact line problems. To remedy the issue of mass change due to the contact angle boundary condition, a source term or Lagrange multiplier is added to the original second-order Phase-Field models, which is determined by the consistent and conservative volume distribution algorithm so that the summation of the order parameters and the consistency of reduction are not influenced. To physically couple the proposed formulation to the hydrodynamics, especially for large-density-ratio problems, the consistent formulation is employed. The reduction-consistent conservative Allen-Cahn models are chosen as examples to illustrate the application of the proposed formulation. The numerical scheme that preserves the consistency and conservation of the proposed formulation is employed to demonstrate its effectiveness. Results produced by the proposed formulation are in good agreement with the exact and/or asymptotic solutions. The proposed method captures complex dynamics of moving contact line problems having large density ratios.
Optimization of X-ray tomography through a cooperative computing system in grid
Cooperative Computing implemented as Cooperative Computing System (CCS) in grid has been proved a considerably reliable technique to execute the tasks with real time constraints in a grid environment. This technique can be applied in many high performance distributed computing applications. HPC has a large number of applications in various fields of physics. One such application in radiation physics is X-ray tomography. X-Ray tomography contains numerous applications in various fields of science, technology and research. As the technology is changing from analog to digital in almost all the scenarios, this paper presents an idea towards the attachment of X-ray tomography assembly to HPC environment so as to obtain the highly reliable optimization.
Overview of the distributed image processing infrastructure to produce the Legacy Survey of Space and Time
The Vera C. Rubin Observatory is preparing to execute the most ambitious astronomical survey ever attempted, the Legacy Survey of Space and Time (LSST). Currently the final phase of construction is under way in the Chilean Andes, with the Observatory’s ten-year science mission scheduled to begin in 2025. Rubin’s 8.4-meter telescope will nightly scan the southern hemisphere collecting imagery in the wavelength range 320–1050 nm covering the entire observable sky every 4 nights using a 3.2 gigapixel camera, the largest imaging device ever built for astronomy. Automated detection and classification of celestial objects will be performed by sophisticated algorithms on high-resolution images to progressively produce an astronomical catalog eventually composed of 20 billion galaxies and 17 billion stars and their associated physical properties. In this article we present an overview of the system currently being constructed to perform data distribution as well as the annual campaigns which reprocess the entire image dataset collected since the beginning of the survey. These processing campaigns will utilize computing and storage resources provided by three Rubin data facilities (one in the US and two in Europe). Each year a Data Release will be produced and disseminated to science collaborations for use in studies comprising four main science pillars: probing dark matter and dark energy, taking inventory of solar system objects, exploring the transient optical sky and mapping the Milky Way. Also presented is the method by which we leverage some of the common tools and best practices used for management of large-scale distributed data processing projects in the high energy physics and astronomy communities. We also demonstrate how these tools and practices are utilized within the Rubin project in order to overcome the specific challenges faced by the Observatory.