Cost-benefit based assurance planning
We have extended an existing risk management framework with a refined cost-benefit model. Benefits are measured in terms of reduction of risk.
SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
We have extended an existing risk management framework with a refined cost-benefit model. Benefits are measured in terms of reduction of risk.
Characterizing internal structures and defects in materials is a challenging task, often requiring solutions to inverse problems with unknown topology, geometry, material properties, and nonlinear deformation. Here, we present a general framework based on physics-informed neural networks for identifying unknown geometric and material parameters. By using a mesh-free method, we parameterize the geometry of the material using a differentiable and trainable method that can identify multiple structural features. We validate this approach for materials with internal voids/inclusions using constitutive models that encompass the spectrum of linear elasticity, hyperelasticity, and plasticity. We predict the size, shape, and location of the internal void/inclusion as well as the elastic modulus of the inclusion. Our general framework can be applied to other inverse problems in different applications that involve unknown material properties and highly deformable geometries, targeting material characterization, quality assurance, and structural design.
The overall project goal was to quantify the trends and variability for Net ecosystem exchange of CO 2 , H 2 O, and energy by northeastern forests, with particular attention to the role of succession, differences in species composition, legacies of past land use, and disturbances. Measurements included flux measurements and observations of biomass accumulation using ecosystem modeling as a framework for data interpretation. Continuation of the long-term record at the Environmental Measurement Site (EMS) Tower was a priority. The final quality-assured CO 2 -flux data now extend through 2010. Data through 2011 are collected but not yet finalized. Biomass observations on the plot array centered on the tower are extended to 2011. Two additional towers in a hemlock stand (HEM) and a younger deciduous stand (LPH) complement the EMS tower by focusing on stands with different species composition or age distribution and disturbance history, but comparable climate and soil type. Over the period since 1993 the forest has added 24.4 Mg-C ha -1 in the living trees. Annual net carbon uptake had been increasing from about 2 Mg-C ha -1 y -1 in the early 1990s to nearly 6 Mg-C ha -1 y -1 by 2008, but declined in 2009-2010. We attribute the increasing carbon uptake to a combination of warmer temperatures, increased photosynthetic efficiency, and increased influence by subcanopy hemlocks that are active in the early spring and late autumn when temperatures are above freezing but the deciduous canopy is bare. Not all of the increased carbon accumulation was found in woody biomass. Results from a study using data to optimize parameters in an ecosystem process model indicate that significant changes in model parameters for photosynthetic capacity and shifts in allocation to slow cycling soil organic matter are necessary for the model to match the observed trends. The emerging working hypothesis is that the pattern of increasing carbon uptake over the early 2000's represents a transient pulse that will eventually end as decomposition of the accumulated carbon catches up.
This Quality Assurance Plan (QAP) provides the overall quality assurance (QA) requirements and general quality practices to be applied to the U.S. Department of Energy (DOE), National Nuclear Security Administration Nevada Site Office (NNSA/NSO) Underground Test Area (UGTA) activities. The requirements in this QAP are consistent with DOE Order 414.1C, Quality Assurance (DOE, 2005); U.S. Environmental Protection Agency (EPA) Guidance for Quality Assurance Project Plans for Modeling (EPA, 2002); and EPA Guidance on the Development, Evaluation, and Application of Environmental Models (EPA, 2009). NNSA/NSO, or designee, must review this QAP every two years. Changes that do not affect the overall scope or requirements will not require an immediate QAP revision but will be incorporated into the next revision cycle after identification. Section 1.0 describes UGTA objectives, participant responsibilities, and administrative and management quality requirements (i.e., training, records, procurement). Section 1.0 also details data management and computer software requirements. Section 2.0 establishes the requirements to ensure newly collected data are valid, existing data uses are appropriate, and environmental-modeling methods are reliable. Section 3.0 provides feedback loops through assessments and reports to management. Section 4.0 provides the framework for corrective actions. Section 5.0 provides references for this document.
Purpose: To establish a new mathematical framework for radiotherapy treatment optimization with voxel-dependent optimization parameters. Methods: In the treatment plan optimization problem for radiotherapy, a clinically acceptable plan is usually generated by an optimization process with weighting factors or reference doses adjusted for a set of the objective functions associated to the organs. Recent discoveries indicate that adjusting parameters associated with each voxel may lead to better plan quality. However, it is still unclear regarding the mathematical reasons behind it. Furthermore, questions about the objective function selection and parameter adjustment to assure Pareto optimality as well as the relationship between the optimal solutions obtained from the organ-based and voxel-based models remain unanswered. To answer these questions, the authors establish in this work a new mathematical framework equipped with two theorems. Results: The new framework clarifies the different consequences of adjusting organ-dependent and voxel-dependent parameters for the treatment plan optimization of radiation therapy, as well as the impact of using different objective functions on plan qualities and Pareto surfaces. The main discoveries are threefold: (1) While in the organ-based model the selection of the objective function has an impact on the quality of the optimized plans, this is no longer an issue for the voxel-based model since the Pareto surface is independent of the objective function selection and the entire Pareto surface could be generated as long as the objective function satisfies certain mathematical conditions; (2) All Pareto solutions generated by the organ-based model with different objective functions are parts of a unique Pareto surface generated by the voxel-based model with any appropriate objective function; (3) A much larger Pareto surface is explored by adjusting voxel-dependent parameters than by adjusting organ-dependent parameters, possibly allowing for the generation of plans with better trade-offs among different clinical objectives. Conclusions: The authors have developed a mathematical framework for radiotherapy treatment optimization using voxel-based parameters. The authors can improve the plan quality by adjusting voxel-based weighting factors and exploring the unique and large Pareto surface which include all the Pareto surfaces that can be generated by organ-based model using different objective functions.
This Quality Assurance Plan (QAP) provides the overall quality assurance (QA) requirements and general quality practices to be applied to the U.S. Department of Energy (DOE), National Nuclear Security Administration Nevada Field Office (NNSA/NFO) Underground Test Area (UGTA) activities. The requirements in this QAP are consistent with DOE Order 414.1D, Change 1, Quality Assurance (DOE, 2013a); U.S. Environmental Protection Agency (EPA) Guidance for Quality Assurance Project Plans for Modeling (EPA, 2002); and EPA Guidance on the Development, Evaluation, and Application of Environmental Models (EPA, 2009). If a participant’s requirement document differs from this QAP, the stricter requirement will take precedence. NNSA/NFO, or designee, must review this QAP every two years. Changes that do not affect the overall scope or requirements will not require an immediate QAP revision but will be incorporated into the next revision cycle after identification. Section 1.0 describes UGTA objectives, participant responsibilities, and administrative and management quality requirements (i.e., training, records, procurement). Section 1.0 also details data management and computer software requirements. Section 2.0 establishes the requirements to ensure newly collected data are valid, existing data uses are appropriate, and environmental-modeling methods are reliable. Section 3.0 provides feedback loops through assessments and reports to management. Section 4.0 provides the framework for corrective actions. Section 5.0 provides references for this document.
Process-related changes during metal additive manufacturing introduce microstructural variability in the material properties of printed parts, directly affecting component reliability. Accurate estimation of these property variations with part performance are essential for quality assurance. Ultrasound testing offers a non-destructive means to estimate mechanical properties and detect defects; however, conventional analysis methods often neglect the influence of microstructural variability, limiting their effectiveness. Here, this research presents a Bayesian inference technique for quantifying wave speed uncertainty from ultrasound measurements of metal additive manufactured parts. By integrating prior ultrasound data with a Bayesian model, the proposed approach generates posterior density estimates of wave speed that systematically account for manufacturing-induced variability and uncertainty. The novelty of this research lies in applying a Bayesian framework to analyze experimental ultrasound measurements within the context of metal additive manufacturing variability. The method enhances the accuracy of wave speed estimation by 64%, defect position by 50% and increases confidence associated with wave speed variance by 30% across different porosity levels, thereby providing a robust foundation for improved decision-making and increased reliability in additively manufactured components.
This report is a continuation of the series of Hunter Dose Tracking System (HDTS) Quality Assurance documents including (Foley and Powell, 2010; Dixon, 2012; Whiteside, 2017b). In this report we have created a suite of automated test cases and a system to analyze the results of those tests as well as documented the methodology to ensure the field system performs within specifications. The software test cases cover all of the functions and interactions of functions that are practical to test. With the developed framework, if software defects are discovered, it will be easy to create one or more test cases to reproduce the defect and ensure that code changes correct the defect.
Qualified modeling and simulation tools and experimental data are needed to provide a reasonable basis for the incorporation of realistic wasteform retention assumptions (i.e., those without orders-of-magnitude conservatism) into performance assessments and regulatory decisions. Use of highly conservative assumptions in performance assessments has historically led to the overprediction of release and near-field transport by as much as 4- to 6-orders of magnitude thereby limiting the nature and quantities of certain contaminants of concern in near surface disposal facilities. This project provides peer-reviewed models and characterization methods to provide more reasonable assumptions for use in performance assessments and regulatory decisions. Simulations tools have been developed to predict hydraulic and chemical performance of waste-forms and barriers used in nuclear applications under several important aging and degradation scenarios, including sulfate attack, carbonation, oxidation, cracking, and leaching; these tools are complaint with DOE Order 414.1D and ASME NQA-1. Wasteform characterization methods have been developed that are consistent with US EPA's Leaching Environmental Assessment Framework (LEAF) currently part of EPA's Hazardous Waste Test Methods (SW-846); the resulting experimental data are evaluated using LeachXS. ORCHESTRA models, that can be called seamlessly from LeachXS, have been developed representing both laboratory and field conditions; these models have undergone an extensive Software Quality Assurance process where they have been calibrated (where necessary), verified, and validated to be compliant with relevant guidelines. The models used for field predictions have also been incorporated into the Cementitious Barriers Partnership (CBP) Software Toolbox that allows probabilistic evaluation of field scenarios. The foci over the next year will be on providing 1) a mechanistic basis for projecting the retention of Tc-99, I-129, and other important radionuclides in near-surface disposal facilities at the Savannah River and Hanford Sites and 2) a technical basis for assessing the efficacy of macro-encapsulation of mercury-contaminated debris at the Oak Ridge Reservation. (authors)
The purpose of this talk is to examine and discuss NASA's basic quality concept, the policy and procedures which define and implement this concept and subsequently explore the NASA-Industry quality relationships which are essential to the success of NASA's quality assurance concept. It is important to emphasize that NASA's Quality Assurance program is predicated on the concept of an individually tailored quality program for each significant NASA procurement - particularly, large space systems. As a result, NASA's Quality Assurance program - to be effective - must be responsive to various technologies, hardware systems, and space missions. In addition, the program must be responsive to changing policies and practices in research, engineering and procurement. Key issues in the NASA-Contractor quality relationships in the framework of an over all NASA-Industry partnership include: (1) the necessity for NASA to effectively discharge its responsibility for providing clear and complete definition of quality requirements at all phases of the procurement cycle; (2) the right of the contractor to expect an explicit definition of NASA quality requirements in each RFP and contract and to request same if it is not provided; (3) the necessity for the contractor to have a dynamic and responsive quality program which is directed towards assuring that the hardware meets all technical requirements and to accomplish this in an effective and efficient manner; and (4) the critical need for investigation and study of the economic aspects of quality and an evaluation of our policies and practices based upon the results of such a study.
The effort and cost required to convert satellite Earth Observation (EO) data into meaningful geophysical variables has prevented the systematic analysis of all available observations. To overcome these problems, we utilise an integrated High Performance Computing and Data environment to rapidly process, restructure and analyse the Australian Landsat data archive. In this approach, the EO data are assigned to a common grid framework that spans the full geospatial and temporal extent of the observations - the EO Data Cube. This approach is pixel-based and incorporates geometric and spectral calibration and quality assurance of each Earth surface reflectance measurement. We demonstrate the utility of the approach with rapid time-series mapping of surface water across the entire Australian continent using 27 years of continuous, 25 m resolution observations. Our preliminary analysis of the Landsat archive shows how the EO Data Cube can effectively liberate high-resolution EO data from their complex sensor-specific data structures and revolutionise our ability to measure environmental change.
To push the modeling and simulation to a new level in simulating realistic problems, a common practice is to couple different single-physics codes together to simulate problems involving multiple physics. Although the method of manufactured solutions (MMS) has been shown to be a powerful tool in code verification, there has been little work on applying MMS to a multi-physics code system. Additionally, due to the scarcity of multi-physics validation data, the significance of code verification becomes more prominent as an important part in software quality assurance. With this, the application of MMS to a coupled code system, e.g. VERA-CS, has become a crucial step, which helps identify bugs affecting the order of accuracy, thus increasing the credibility and reliability of the code. In this work, we investigate the application of MMS to verify a multi-physics code system and establish a framework for this application, and we demonstrate this with a neutronics code coupled with a thermal hydraulics (TH) code. The convection module is not yet added to this work, so by TH, only conduction is considered.
Computational tools have a crucial role to play in accelerating the deployment of fusion as a clean, reliable, abundant, and sustainable energy source. Multiphysics, high-fidelity simulation capabilities can help model, study, and predict intricate interactions between materials performance, plasma exposure, neutron irradiation, and engineering processes. As such, they can assist in the resolution of scientific and engineering challenges underpinning design, construction, and commission of fusion power plants. To address these needs, ongoing efforts are leveraging the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework and delivering new computational tools for the fusion community. These tools inherit crucial attributes from MOOSE. They are open-source, modular, integrated with nuclear industry-standard software quality assurance processes, and enable multiphysics, multi-fidelity, fully integrated, zero- to three-dimensional, and massively parallel simulations. After a short overview of these capabilities, we will present the development of Fusion ENergy Integrated multiphys-X (FENIX), a MOOSE-based application designed to enable plasma facing component design and performance evaluation. Throughout their lifetime, plasma facing components are exposed to extreme thermal loads, repeated thermal shocks, and irradiation by plasma ions, neutral particles, and high-energy neutrons. Consequently, designing a plasma facing component with acceptable lifetime degradation is extremely challenging. FENIX aims to model the multiphysics environment in which plasma facing components evolve to accelerate their design studies. To that end, FENIX couples existing MOOSE capabilities such as heat transfer, thermomechanics, and thermal hydraulics, with tritium transport via the MOOSE-based Tritium Migration Analysis Program, Version 8 (TMAP8), with neutronics via the MOOSE-based high-fidelity neutron-photon transport and fluid dynamics code Cardinal, and finally with Particle-in-Cell plasma simulation capabilities being developed in this project. In this study, we present the current FENIX capabilities and preliminary results of its application to model the Tritium Plasma Experiment set up at Idaho National Laboratory.
Life Cycle Assessment (LCA) is a structured, comprehensive method of quantifying material- and energy-flows and their associated emissions caused in the life cycle of goods and services. The ISO 14040 and 14044 standards provide the framework for LCA. However, this framework leaves the individual practitioner with a range of choices that can affect the results and thus the conclusions of an LCA study. The current IEA guidelines were developed to provide guidance on assuring consistency, balance, and quality to enhance the credibility and reliability of the results from LCAs on photovoltaic (PV) electricity generation systems. The guidelines represent a consensus among the authors - PV LCA experts in North America, Europe, and Asia - for assumptions made on PV performance, decisions on process input and emissions allocation, methods of analysis, and reporting of the results. Guidance is given on PV-specific parameters used as inputs in LCA and on choices and assumptions in life cycle inventory (LCI) data analysis and on implementation of modeling approaches. A consistent approach towards system modeling, the functional unit, the system boundaries, water use modeling and the allocation aspects enhances the credibility of PV electricity LCA studies and enables balanced LCA-based comparisons of different electricity producing technologies. The document discusses metrics like greenhouse gas emissions (GHG), cumulative energy demand (CED), acidification potential (AP), ozone depletion potential (ODP), human toxicity, ecotoxicity and ionizing radiation. Guidance is given for the definition of the energy payback time (EPBT), the nonrenewable energy payback time (NREPBT), and the impact mitigation potentials (IMP). The indicator energy return on investment (EROI) is described in a separate International Energy Agency (IEA) PV Power Systems (PVPS) Task 12 report (Raugei et al. 2015). The guidelines on the reporting and communication of the results serve the need for producing clear, comprehensive and transparent reports.
Underground test coordination is a critical component of safe and efficient conduct of testing operations in a working underground research laboratory (URL). This is particularly important when planning and implementing large, multi-organizational field-scale test programs, when the URL is co-located with an operating repository, or when the host facility, such as the Waste Isolation Pilot Plant (WIPP), is recovering from off-normal events. As such, the Department of Energy Carlsbad Field Office developed an Integrated Project Team (IPT) charter in late 2013 establishing the WIPP underground Test Coordination Office (TCO). The IPT was established to ensure that underground science activities are coordinated, implemented, and managed in an integrated, consistent, efficient, cost-effective, safe, and environmentally compliant manner that maintains quality assurance standards. This is done while ensuring testing operations do not interfere with the WIPP's primary mission, the disposal of transuranic (TRU) waste, and at present, the recovery of WIPP operations. This paper reports the current status of the WIPP underground science and testing programs within the framework of the WIPP stabilization and recovery activities and describes the role of the TCO for current activities as well as for the long-term success of an underground research laboratory. As a result of the underground fire and radiological incident of early February 2014, during this recent period of WIPP recovery, the TCO is ensuring the requirements of the scientific programs are met and that work activities are planned and implemented in compliance with enhanced work control processes and corrective actions imposed at WIPP. This paper addresses the impacts of the accidents at WIPP on the many science experiments that were in process when the events occurred. It presents the plans for their recovery in concert with WIPP's recovery plans, and summarizes the impacts of new underground processes and procedures that will be imposed on the science work as a result. (authors)
Net Energy Analysis (NEA) is a structured, comprehensive method of quantifying the extent to which a given energy source is able to provide a net energy gain (i.e., an energy surplus) to the end user, after accounting for all the energy losses occurring along the chain of processes that are required to exploit it (i.e., for its extraction, processing and transformation into a usable energy carrier, and delivery to the end user), as well as for all the additional energy 'investments' that are required in order to carry out the same chain of processes. However, this general framework leaves the individual practitioner with a range of choices that can affect the results and thus, the conclusions of a NEA study. The current IEA PVPS guidelines were developed to provide guidance on assuring consistency, balance, and quality to enhance the credibility and reliability of the results from photovoltaic (PV) NEAs. The guidelines represent a consensus among the authors - PV NEA experts in North America and Europe - for assumptions made on PV performance, process inputs and outputs, methods of analysis, and reporting of the results. Guidance is given on photovoltaic-specific parameters used as inputs in NEA and on choices and assumptions in inventory data analysis and on implementation of modelling approaches. A consistent approach towards system modelling, the functional unit, the system boundaries and allocation aspects enhance the credibility of PV electricity NEA studies and enables balanced NEA-based comparisons. Specifically, "apples-to-oranges" comparisons of different energy carriers (e.g., fuels vs. electricity) are not methodologically sound and are to be avoided in all cases; also, any comparison across renewable and non-renewable electricity generation technologies must clearly point out the intrinsically short-term nature of the NEA viewpoint, which does not capture the long-term sustainability implications of renewable vs. non-renewable primary energy harvesting and use: non-renewable primary energy resources are depleted and finally exhausted (irrespective of the size of the EROI), while renewable primary energy resources are not. This document provides an in-depth discussion of a common metric of NEA, namely the energy return on investment (EROI), and how this is to be interpreted vis-a-vis the deceptively similar-sounding metrics in the field of Life Cycle Assessment (LCA): cumulative energy demand (CED) and non-renewable cumulative energy demand (nr-CED) per unit output. Specifically, a number of key differences are highlighted between these metrics as applied to electricity production systems, which are listed in Table S-1.
Net Energy Analysis (NEA) is a structured, comprehensive method of quantifying the extent to which a given energy source is able to provide a net energy gain (i.e., an energy surplus) to the end user, after accounting for all the energy losses occurring along the chain of processes that are required to exploit it (i.e., for its extraction, processing and transformation into a usable energy carrier, and delivery to the end user), as well as for all the additional energy 'investments' that are required in order to carry out the same chain of processes. However, this general framework leaves the individual practitioner with a range of choices that can affect the results and thus, the conclusions of a NEA study. The current IEA PVPS guidelines were developed to provide guidance on assuring consistency, balance, and quality to enhance the credibility and reliability of the results from photovoltaic (PV) NEAs. The guidelines represent a consensus among the authors -- PV NEA experts in North America, Europe, and Asia -- for assumptions made on PV performance, process inputs and outputs, methods of analysis, and reporting of the results. Guidance is given on photovoltaic-specific parameters used as inputs in NEA and on choices and assumptions in inventory data analysis and on implementation of modelling approaches. A consistent approach towards system modelling, the functional unit, the system boundaries and allocation aspects enhances the credibility of PV electricity NEA studies and enables balanced NEA-based comparisons of different electricity producing technologies. This document provides an in-depth discussion of a common metric of NEA, namely the energy return on investment (EROI), and how this is to be interpreted vis-a-vis the deceptively similar-sounding metrics in the field of Life Cycle Assessment (LCA): cumulative energy demand (CED) and non-renewable cumulative energy demand (nr-CED) per unit output. Specifically, a number of key differences are highlighted between these metrics as applied to electricity production systems. Transparency in reporting is of the utmost importance as parameters vary with geographical zones, and a system's boundary conditions and modelling approach can affect the findings significantly. This guideline lists 16 items that should be reported in every NEA study of PV electricity.
Purpose: This study provides an overview of the design and commissioning of the Monte Carlo (MC) model of the spot-scanning proton therapy nozzle and its implementation for the patient plan simulation. Methods: The Hitachi PROBEAT V scanning nozzle was simulated based on vendor specifications using the TOPAS extension of Geant4 code. FLUKA MC simulation was also utilized to provide supporting data for the main simulation. Validation of the MC model was performed using vendor provided data and measurements collected during acceptance/commissioning of the proton therapy machine. Actual patient plans using CT based treatment geometry were simulated and compared to the dose distributions produced by the treatment planning system (Varian Eclipse 13.6), and patient quality assurance measurements. In-house MATLAB scripts are used for converting DICOM data into TOPAS input files. Results: Comparison analysis of integrated depth doses (IDDs), therapeutic ranges (R90), and spot shape/sizes at different distances from the isocenter, indicate good agreement between MC and measurements. R90 agreement is within 0.15 mm across all energy tunes. IDDs and spot shapes/sizes differences are within statistical error of simulation (less than 1.5%). The MC simulated data, validated with physical measurements, were used for the commissioning of the treatment planning system. Patient geometry simulations were conducted based on the Eclipse produced DICOM plans. Conclusion: The treatment nozzle and standard option beam model were implemented in the TOPAS framework to simulate a highly conformal discrete spot-scanning proton beam system.