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The International Space Station Systems Engineering and Integration Office is responsible for the Multilateral International Space Station (ISS) and ISS Visiting Vehicle Jettison Policy, the Partner Program Directive on jettisoning objects from the ISS and Visiting Vehicles to/from the ISS.
Symbolic execution is a program analysis technique that is used for many purposes, one of which is test-case generation. For loop-free programs, this generates a test-set that achieves path coverage. Program loops, however, imply exponential growth of the number of paths in the best case and non-termination in the worst case. In practice, the number of loop unwindings needs to be bounded for analysis. We consider symbolic execution in the context of the tool Symbolic Pathfinder. This tool extends the model-checker Java Pathfinder and relies on its bounded state-space exploration for termination. We present an implementation of k-bounded loop unwinding, which increases the amount of user-control over the symbolic execution of loops. Bounded unwinding can be viewed as a naive way to prune paths through loops. When using symbolic execution for test-case generation, naively pruning paths is likely at the cost of coverage. In order to improve coverage of branches within a loop body, we present a technique that semi-automatically concretizes variables used in a loop. The basic technique is limited and we therefore present annotations to manually steer symbolic execution towards certain branches, as well as ideas on how the technique can be extended to be more widely applicable.
Here, quantum computing (QC) has experienced rapid growth in recent years with the advent of robust programming environments, readily accessible software simulators and cloud-based QC hardware platforms, and growing interest in learning how to design useful methods that leverage this emerging technology for practical applications. From the perspective of the field of visualization, this article examines research challenges and opportunities along the path from initial feasibility to practical use of QC platforms applied to meaningful problems.
The main thrust of this project was to devise a method by which the majority of North Slope of Alaska (NSA) meteorological and radiometric data, collected on a daily basis, could be used to evaluate and improve global climate model (GCM) simulations and their parameterizations, particularly for cloud microphysics. Although the standard ARM Program sensors for a less complete suite of instruments for cloud and aerosol studies than the instruments on an intensive field program such as the 2008 Indirect and Semi-Direct Aerosol Campaign (ISDAC), the advantage they offer lies in the long time base and large volume of data that covers a wide range of meteorological and climatological conditions. The challenge has been devising a method to interpret the NSA data in a practical way, so that a wide variety of meteorological conditions in all seasons can be examined with climate models. If successful, climate modelers would have a robust alternative to the usual “case study” approach (i.e., from intensive field programs only) for testing and evaluating their parameterizations’ performance. Understanding climate change on regional scales requires a broad scientific consideration of anthropogenic influences that goes beyond greenhouse gas emissions to also include aerosol-induced changes in cloud properties. For instance, it is now clear that on small scales, human-induced aerosol plumes can exert microclimatic radiative and hydrologic forcing that rivals that of greenhouse gas–forced warming. This project has made significant scientific progress by investigating what causes successive versions of climate models continue to exhibit errors in cloud amount, cloud microphysical and radiative properties, precipitation, and radiation balance, as compared with observations and, in particular, in Arctic regions. To find out what is going wrong, we have tested the models' cloud representation over the full range of meteorological conditions found in the Arctic using the ARM North Slope of Alaska (NSA) data.
Nonconvex, nonlinear optimization problems arise naturally in parameter fitting and machine learning. While augmented Lagrangian methods have demonstrated robust convergence for classes of these problems, their convergence for block updates has been relatively unexplored outside of the context of the alternating direction method of multipliers (ADMM). ADMM has seen extensive use in these applications, but may exhibit uncertain convergence behavior in many practical nonconvex settings, and struggles with general nonlinear constraints. In contrast, filter methods have proved effective in enforcing convergence for sequential quadratic programming methods and interior point methods with feasibility criteria. We develop an ADMM-filter method for highly nonlinear and nonconvex problems. Here, we show convergence under mild assumptions for several types of coordinate descent schemes, and demonstrate our algorithm on nonnegative matrix factorization and completion problems in imaging and chemical spectrum analysis.
Strategic environmental assessment (SEA) has become an increasingly important decision-support tool for providing information on the environmental implications of a policy, plan, or program. The goal is to safeguard the environment and promote sustainable development at the strategic level. Despite major progress in implementing SEA practices internationally, developing countries, such as China, often lag behind in applying SEA methodology. Lack of available data and time constraints arising from tight schedules create problems. The rapid impact assessment matrix (RIAM) is a potential resource for breaking through such difficulties. Our analysis of RIAM applications suggested that it could become a tool for evaluating strategic alternatives because of its applicability in interdisciplinary settings, its transparency, and its short implementation timeframe. To make it more suitable for the SEA context, we have developed two major improvements to the conventional RIAM process: assignment of weights to assessment indicators and the development of an integrated environmental assessment score (IES). The improved RIAM process was employed in an SEA of the development plan for the Nansha District in Guangzhou, the capital city of Guangdong Province in China. It was used to assess five alternatives for development in Wanqingsha (WQS), a subunit of Nansha, where important ecological resources are located and where industrial development could impact the air quality in the neighboring Hong Kong Special Administrative Region (HKSAR). The evaluation identified WQS-A04 as the preferred alternative. This alternative involved a minimal amount of industrial development – 10% compared with the most intense development alternative – and included important wetland preservation plans. The assessment results have been incorporated into the officially approved development plan for Nansha. The improved RIAM methodology is well adapted to the technical aims of SEA and decision-making structures in China. It offers the potential for delivering timely and quality results to decision-making processes. To achieve the desired efficiency, it is recommended that an SEA procedure take into account findings acquired from an improved RIAM application at an early stage, then, at a later stage, results from more comprehensive assessments conducted using more sophisticated methods should be added, if time and data are available. - Highlights: • RIAM is a potential SEA tool due to its multidisciplinary setting and rapid process. • Weighting index and computing IES are raised for improving RIAM when applied to SEAs. • The improved RIAM boosts SEA effectiveness by timely responding to decision-making. • The improved RIAM is more suitable to an SEA bothered by tight time or data shortage. • The improved RIAM adapts to the technical aims of SEA and decision features in China.
Purpose: Rapid evolution of imaging technologies and their integration into radiation therapy practice demands that radiation oncology (RO) training curricula be updated. The purpose of this study was to develop an entry-to-practice image literacy competency profile. Methods and Materials: A list of 263 potential imaging competency items were assembled from international objectives of training. Expert panel eliminated redundant or irrelevant items to create a list of 97 unique potential competency items. An international 2-round Delphi process was conducted with experts in RO. In round 1, all experts scored, on a 9-point Likert scale, the degree to which they agreed an item should be included in the competency profile. Items with a mean score ≥7 were included, those 4 to 6 were reviewed in round 2, and items scored <4 were excluded. In round 2, items were discussed and subsequently ranked for inclusion or exclusion in the competency profile. Items with >75% voting for inclusion were included in the final competency profile. Results: Forty-nine radiation oncologists were invited to participate in round 1, and 32 (65%) did so. Participants represented 24 centers in 6 countries. Of the 97 items ranked in round 1, 80 had a mean score ≥7, 1 item had a score <4, and 16 items with a mean score of 4 to 6 were reviewed and rescored in round 2. In round 2, 4 items had >75% of participants voting for inclusion and were included; the remaining 12 were excluded. The final list of 84 items formed the final competency profile. The 84 enabling competency items were aggregated into the following 4 thematic groups of key competencies: (1) imaging fundamentals (42 items); (2) clinical application (27 items); (3) clinical management (5 items); and (4) professional practice (10 items). Conclusions: We present an imaging literacy competency profile which could constitute the minimum training standards in radiation oncology residency programs.
Twenty-first century power systems, with higher penetration levels of low-carbon energy, smart grids, and other emerging technologies, will favor resources that have low marginal costs and provide system flexibility (e.g., the ability to cycle on and off to follow changes in variable renewable energy plant output). Questions remain about both the fate of coal plants in this scenario and whether they can cost-effectively continue to operate if they cycle routinely. The experience from the CGS plant demonstrates that coal plants can become flexible resources. This flexibility - namely the ability to cycle on and off and run at lower output (below 40% of capacity) - requires limited hardware modifications but extensive modifications to operational practice. Cycling does damage the plant and impact its life expectancy compared to baseload operations. Nevertheless, strategic modifications, proactive inspections and training programs, among other operational changes to accommodate cycling, can minimize the extent of damage and optimize the cost of maintenance. CGS's cycling, but not necessarily the associated price tag, is replicable. Context - namely, power market opportunities and composition of the generation fleet - will help determine for other coal plants the optimal balance between the level of cycling-related forced outages and the level of capital investment required to minimize those outages. Replicating CGS's experience elsewhere will likely require a higher acceptance of forced outages than regulators and plant operators are accustomed to; however, an increase in strategic maintenance can minimize the impact on outage rates.
The Department of Energy (DOE) has made significant progress developing simulation tools to predict the behavior of nuclear systems with greater accuracy and of increasing our capability to predict the behavior of these systems outside of the standard range of applications. These analytical tools require a more complex array of validation tests to accurately simulate the physics and multiple length and time scales. Results from modern simulations will allow experiment designers to narrow the range of conditions needed to bound system behavior and to optimize the deployment of instrumentation to limit the breadth and cost of the campaign. Modern validation, verification and uncertainty quantification (VVUQ) techniques enable analysts to extract information from experiments in a systematic manner and provide the users with a quantified uncertainty estimate. Unfortunately, the capability to perform experiments that would enable taking full advantage of the formalisms of these modern codes has progressed relatively little (with some notable exceptions in fuels and thermal-hydraulics); the majority of the experimental data available today is the "historic" data accumulated over the last decades of nuclear systems R&D. A validated code-model is a tool for users. An unvalidated code-model is useful for code developers to gain understanding, publish research results, attract funding, etc. As nuclear analysis codes have become more sophisticated, so have the measurement and validation methods and the challenges that confront them. A successful yet cost-effective validation effort requires expertise possessed only by a few, resources possessed only by the well-capitalized (or a willing collective), and a clear, well-defined objective (validating a code that is developed to satisfy the need(s) of an actual user). To that end, the Idaho National Laboratory established the Nuclear Energy Knowledge and Validation Center to address the challenges of modern code validation and to manage the knowledge from past, current, and future experimental campaigns. By pulling together the best minds involved in code development, experiment design, and validation to establish and disseminate best practices and new techniques, the Nuclear Energy Knowledge and Validation Center (NEKVaC or the ‘Center’) will be a resource for industry, DOE Programs, and academia validation efforts.
This report is an FY21 Deliverable for NA-21.1, International Nuclear Security, WBS 21.1.1.1.4 Counter Unmanned Aircraft Systems (CUAS), under C.1.4, Develop Suite of Engagement Materials and Tools for Country/Regional Teams. The responsibility for protecting nuclear assets is an immense challenge for governments. Policy changes based on geopolitics, instability of government regimes, and technological advances that facilitate theft of nuclear material all contribute to the enduring task of staying current with these and other threats. One of the recent threats to come along is the use of drones or Unmanned Aircraft Systems (UAS) to circumvent traditional Physical Security Systems. There are significant resources invested on physical protection systems for securing nuclear assets, but many of these systems can now be bypassed by simply flying over these measures intended to guard against ground attacks. In recent years the threat increased to hostile groups to attack or surveil due to advances and availability of UAS platforms. It is now more urgent to implement systems and procedures to counter the UAS threat. The United States (U.S.) federal government granted authority to the Department of Energy (DOE) to implement a Counter UAS to protect nuclear assets. This document provides a very practical and transparent view of the trials, tribulations and challenges we encountered while implementing the first Counter-Unmanned Aircraft System (CUAS) Program in the DOE at Los Alamos National Laboratory (LANL).
The objective of the Photovoltaic Collaborative to Advance Multi-climate and Performance Research (PVCAMPER) is to create a multi-climate research platform similar to the US DOE Regional Test Center (RTC) program. Overall, the goal is to foster collaborative research and to build an international organization dedicated to sharing data and exchanging best practices related to PV performance.
The DECOVALEX Project is an on-going international research collaboration, established in 1992, to advance the understanding and modeling of coupled Thermal (T), Hydrological (H), Mechanical (M) and Chemical (C) processes in geological in geological systems. This document is the final report of Task G which was proposed by the Swedish Radiation Safety Authority (SSM) and coordinated by geomecon GmbH, presenting the technical definitions of the problems studied, approaches applied, achievements made and outstanding issues for future research. Task G in DECOVALEX-2019 is primarily concerned with the evolution of transmissivity throughout the lifetime of a repository for radioactive waste, and in particular of spent nuclear fuel, in sparsely fractured and competent crystalline rock masses, and the representation of these processes via numerical simulation. The numerical simulations were to be evaluated for their suitability, and to be validated. Over the course of the work presented here, not only were transmissivity changes and the best approaches to simulate those change examined, but also strategies were to be developed on how to monitor transmissivity change. Guidelines on what a control program and a monitoring system for a repository should include and be able to measure, and how this can be done in practice, was a key objective of the research project.
Sandia National Laboratories, hereinafter referred to as Sandia, is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration. This Annual Site Environmental Report was prepared in accordance with and as required by DOE O 231.1B, Admin Change 1, Environment, Safety and Health Reporting , and is approved for public release. The U.S. Department of Energy (DOE) and its management and operating contractor for Sandia are committed to safeguarding the environment, continually assessing sustainability practices, and ensuring the validity and accuracy of the monitoring data presented here. This report summarizes the environmental protection, restoration, and monitoring programs in place for Sandia National Laboratories, New Mexico (SNL/NM), during calendar year 2020.
The U.S. Department of Energy Solar Decathlon (DOE/SD) is a collegiate competition, comprising 10 contests, that challenges student teams to design and build highly efficient and innovative buildings powered by renewable energy. The winners will be those teams that best blend architectural and engineering excellence with innovation, market potential, building efficiency, and smart energy production. The DOE/SD is comprised of two Challenges--Design Challenge (annual, in April of each year at NREL in Golden, Colo.) and Build Challenge (biennial, held next in June/July 2020 in Washington D.C.). NREL provides competition management for DOE/SD. For over 35 years, EEBA has provided the most trusted resources for building science information and education in the construction industry. EEBA delivers turn-key educational resources and events designed to transform residential construction practices through high performance design, marketing, materials, and technologies. NREL and EEBA establish this CRADA to enable the success of the DOE/SD program in managing sponsorship funds and creating a professional education program. EEBA acted as an Education Partner to DOE/SD, which included: 1) accepting and dispersing sponsorship funds for DOE/SD; and 2) providing professional development content.
The U.S. Department of Energy Bioenergy Technology Office's (BETO's) 2023 Billion-Ton Report (BT23) is an assessment of renewable carbon resources potentially available in the United States. BT23 explores these resources in terms of quantity, price, geographical density and distribution, and market maturity. Resource quantities in this report are limited by specified economic and environmental sustainability constraints. Good practices are needed to ensure biomass production has positive environmental outcomes. BT23 supports BETO's mission, particularly the 2023 Multi-Year Program Plan. To access 2023 Billion-Ton Report PDFs, appendices, and high-level messages, navigate to the 2023 Billion-Ton Report landing page at https://energy.gov/eere/bioenergy/2023-billion-ton-report-assessment-us-renewable-carbon-resources on the U.S. Department of Energy Bioenergy Technologies Office website. To access information about the quality assumptions used in this report, please see the Biomass Feedstock Library at https://bioenergylibrary.inl.gov/Home/Home.aspx Please cite the 2023 Billion-Ton Report as: U.S. Department of Energy. 2024. 2023 Billion‐Ton Report: An Assessment of U.S. Renewable Carbon Resources. M. H. Langholtz (Lead). Oak Ridge, TN: Oak Ridge National Laboratory. ORNL/SPR-2024/3103. doi: 10.23720/BT2023/2316165. Contact Us
Report presents practical information for incorporating particle impact protection features and average total pressure measurement into probe design while optimizing probe transient response. Computer program calculates probe response, based on Bergh-Tijdeman equation.
Description of an efficient digital computer method for the determination of the propagation of elastic stresses and deformations in certain geometrically nonlinear structures subjected to high impact loading. The finite-element matrix displacement approach utilizing curved quadrilateral shell elements in conjunction with a nodewise predictor-corrector method employing Runge-Kutta extrapolation techniques has been adopted for the present solution. The related computer program written in FORTRAN V for the UNIVAC 1108 computer has proved to be effective for the solution of a range of practical problems including rectangular and cylindrical panels. Numerical results are presented for a relevant structure, the cell container, and the negative electrode of an impact-resistant battery subjected to high impact, simulating its free landing on a planetary surface.
A spectrum of plans has been prepared to illustrate the range of practical sharing possibilities available so as to assist Ames Research Center (ARC) and European Space Research Organization (ESRO) in selection of a program meeting mutual goals. Five plans are described showing increased participation by ESRO WITH ascending plan number. Each of these has sharing properties fulfilling particular requirements such as available ESRO budget level, extent of ESRO program responsibility, matching particular ESRO capability, and cost saving to ARC through sharing. All plans apply to orbiter sharing only. A sharing plan based on the model Plan 4 may offer the most attractive division of Pioneer Venus between ARC and ESRO. This plan allows ESRO to bear primary responsibility for the orbiter and to avoid an extensive financial burden. Savings to ARC are commensurate with ARC loss of program control. Duplication of effort is avoided by using orbiter subsystems that are common to the probe bus and orbiter.