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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

NASA Tech Briefs, January 2012

Contents of this issue are: (1) Energy-Based Tetrahedron Sensor for High-Temperature, High-Pressure Environments (2) Handheld Universal Diagnostic Sensor (3) Large-Area Vacuum Ultraviolet Sensors (4) Fiber Bragg Grating Sensor System for Monitoring Smart Composite Aerospace Structures (5) Health-Enabled Smart Sensor Fusion Technology (6) Extended-Range Passive RFID and Sensor Tags (7) Hybrid Collaborative Learning for Classification and Clustering in Sensor Networks (8) Self-Healing, Inflatable, Rigidizable Shelter (9) Improvements in Cold-Plate Fabrication (10) Technique for Radiometer and Antenna Array Calibration - TRAAC (11) Real-Time Cognitive Computing Architecture for Data Fusion in a Dynamic Environment (12) Programmable Digital Controller (13) Use of CCSDS Packets Over SpaceWire to Control Hardware (14) Key Decision Record Creation and Approval Module (15) Enhanced Graphics for Extended Scale Range (16) Debris Examination Using Ballistic and Radar Integrated Software (17) Data Distribution System (DDS) and Solar Dynamic Observatory Ground Station (SDOGS) (18) Integration Manager (19) Eclipse-Free-Time Assessment Tool for IRIS (20) Automated and Manual Rocket Crater Measurement Software (21) MATLAB Stability and Control Toolbox Trim and Static Stability Module (22) Patched Conic Trajectory Code (23) Ring Image Analyzer (24) SureTrak Probability of Impact Display (25) Implementation of a Non-Metallic Barrier in an Electric Motor (26) Multi-Mission Radioisotope Thermoelectric Generator Heat Exchangers for the Mars Science Laboratory Rover (27) Uniform Dust Distributor for Testing Radiative Emittance of Dust-Coated Surfaces (28) MicroProbe Small Unmanned Aerial System (29) Highly Stable and Active Catalyst for Sabatier Reactions (30) Better Proton-Conducting Polymers for Fuel-Cell Membranes (31) CCD Camera Lens Interface for Real-Time Theodolite Alignment (32) Peregrine 100-km Sounding Rocket Project (33) SOFIA Closed- and Open-Door Aerodynamic Analyses (34) Sonic Thermometer for High-Altitude Balloons (35) Near-Infrared Photon-Counting Camera for High-Sensitivity Observations (36) Integrated Optics Achromatic Nuller for Stellar Interferometry (37) High-Speed Digital Interferometry (38) Ultra-Miniature Lidar Scanner for Launch Range Data Collection (39) Shape and Color Features for Object Recognition Search (40) Explanation Capabilities for Behavior-Based Robot Control (41) A DNA-Inspired Encryption Methodology for Secure, Mobile Ad Hoc Networks (42) Quality Control Method for a Micro-Nano-Channel Microfabricated Device (43) Corner-Cube Retroreflector Instrument for Advanced Lunar Laser Ranging (44) Electrospray Collection of Lunar Dust (45) Fabrication of a Kilopixel Array of Superconducting Microcalorimeters with Microstripline Wiring Spacecraft Attitude Tracking and Maneuver Using Combined Magnetic Actuators (46) Coherent Detector for Near-Angle Scattering and Polarization Characterization of Telescope Mirror Coatings

Source record↗
DOE OSTI2019

Assessment of Physicochemical Properties of Electrical Arc Furnace Slag and Their Effects on Foamability

The composition of slags of an electric arc furnace (EAF) in a commercial melt shop was systematically analyzed with a focus on slag foaming. Basic behavior of FeO in an EAF slag was confirmed using fundamental thermodynamics. Monoxide ([Mg,Fe,Mn]O = M’O) and spinel ([Mg,Fe]Al{sub 2}O{sub 4}) phases in EAF slag were confirmed by X-ray diffraction analysis, and these results were interpreted in the context of equilibrium cooling calculation using FactSage™ software. Furthermore, the distribution of MgO with respect to the M’O-saturation limit at different basicity ratios (=CaO/SiO{sub 2}=C/S) and temperatures was evaluated. In particular, the relationship between MgO and FeO for C/S ratios ranging from 1.3 to 1.6 was considered with reference to phase equilibria. Foam height was affected by slag viscosity (η) and gas generation according to changes in C/S ratio and FeO content. Foaming index (Σ) decreased with the increasing C/S ratio and FeO content. The measured foam heights were relatively higher than the calculated values, and the result indicates that the effect of M’O on slag foaming in commercial process is remarkable. Therefore, slag chemistry should be optimized based on thermodynamic considerations and thermophysical properties to achieve good foaming characteristics.

36 MATERIALS SCIENCE↗
DOE OSTI2010

Surface rheology and interface stability.

We have developed a mature laboratory at Sandia to measure interfacial rheology, using a combination of home-built, commercially available, and customized commercial tools. An Interfacial Shear Rheometer (KSV ISR-400) was modified and the software improved to increase sensitivity and reliability. Another shear rheometer, a TA Instruments AR-G2, was equipped with a du Nouey ring, bicone geometry, and a double wall ring. These interfacial attachments were compared to each other and to the ISR. The best results with the AR-G2 were obtained with the du Nouey ring. A Micro-Interfacial Rheometer (MIR) was developed in house to obtain the much higher sensitivity given by a smaller probe. However, it was found to be difficult to apply this technique for highly elastic surfaces. Interfaces also exhibit dilatational rheology when the interface changes area, such as occurs when bubbles grow or shrink. To measure this rheological response we developed a Surface Dilatational Rheometer (SDR), in which changes in surface tension with surface area are measured during the oscillation of the volume of a pendant drop or bubble. All instruments were tested with various surfactant solutions to determine the limitations of each. In addition, foaming capability and foam stability were tested and compared with the rheology data. It was found that there was no clear correlation of surface rheology with foaming/defoaming with different types of surfactants, but, within a family of surfactants, rheology could predict the foam stability. Diffusion of surfactants to the interface and the behavior of polyelectrolytes were two subjects studied with the new equipment. Finally, surface rheological terms were added to a finite element Navier-Stokes solver and preliminary testing of the code completed. Recommendations for improved implementation were given. When completed we plan to use the computations to better interpret the experimental data and account for the effects of the underlying bulk fluid.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Development of a bayesian belief network model for the software reliability assessment of nuclear digital I and C safety systems - 206

Since the digital instrumentation and control systems are expected to play an important role for the safety systems in nuclear power plants (NPPs), the need has emerged to not only establish a basis for incorporating software behavior into digital I and C system reliability models, but also to quantify the failure probability of the software used in NPP digital protection systems. In this study, a Bayesian belief network (BBN) model is developed to quantitatively assess software reliability by estimating the number of faults in a software program considering its software development life cycle (SDLC). The model structure and parameters are established based on the information applicable to NPP safety-related systems and the evidence used to construct and quantify the BBN model was collected from three stages of expert elicitation. The software failure probability is estimated from the number of residual defects in a software program at the end of SDLC phase. As a case study, the BBN model was applied to quantify the software reliability of a typical digital protection software having the size of 50 function points and having the Medium development and validation and verification (V and V) qualities. The developed model can be applied to estimate the failure probability for both developing and deployed safety-related NPP software, and such results can be used to evaluate the quality of the digital I and C systems in addition to estimating potential reactor risk due to software failure. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Time Dependent Data Mining in RAVEN

RAVEN is a generic software framework to perform parametric and probabilistic analysis based on the response of complex system codes. The goal of this type of analyses is to understand the response of such systems in particular with respect their probabilistic behavior, to understand their predictability and drivers or lack of thereof. Data mining capabilities are the cornerstones to perform such deep learning of system responses. For this reason static data mining capabilities were added last fiscal year (FY 15). In real applications, when dealing with complex multi-scale, multi-physics systems it seems natural that, during transients, the relevance of the different scales, and physics, would evolve over time. For these reasons the data mining capabilities have been extended allowing their application over time. In this writing it is reported a description of the new RAVEN capabilities implemented with several simple analytical tests to explain their application and highlight the proper implementation. The report concludes with the application of those newly implemented capabilities to the analysis of a simulation performed with the Bison code.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

StructuredFuzzer: Fuzzing Structured Text-Based Control Logic Applications

Rigorous testing methods are essential for ensuring the security and reliability of industrial controller software. Fuzzing, a technique that automatically discovers software bugs, has also proven effective in finding software vulnerabilities. Unsurprisingly, fuzzing has been applied to a wide range of platforms, including programmable logic controllers (PLCs). However, current approaches, such as coverage-guided evolutionary fuzzing implemented in the popular fuzzer American Fuzzy Lop Plus Plus (AFL++), are often inadequate for finding logical errors and bugs in PLC control logic applications. They primarily target generic programming languages like C/C++, Java, and Python, and do not consider the unique characteristics and behaviors of PLCs, which are often programmed using specialized programming languages like Structured Text (ST). Furthermore, these fuzzers are ill suited to deal with complex input structures encapsulated in ST, as they are not specifically designed to generate appropriate input sequences. This renders the application of traditional fuzzing techniques less efficient on these platforms. To address this issue, this paper presents a fuzzing framework designed explicitly for PLC software to discover logic bugs in applications written in ST specified by the IEC 61131-3 standard. The proposed framework incorporates a custom-tailored PLC runtime and a fuzzer designed for the purpose. We demonstrate its effectiveness by fuzzing a collection of ST programs that were crafted for evaluation purposes. We compare the performance against a popular fuzzer, namely, AFL++. The proposed fuzzing framework demonstrated its capabilities in our experiments, successfully detecting logic bugs in the tested PLC control logic applications written in ST. On average, it was at least 83 times faster than AFL++, and in certain cases, for example, it was more than 23,000 times faster.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Implementation of a feature selection algorithm in FARM to identify important state variables and time-invariant matrices

The FARM (Feasible Actuator Range Modifier) software module is a component of the RAVEN-based FORCE framework for analysis of Integrated Energy Systems (IES). FARM aids the HERON software module in the evaluation of the optimal dispatch for the different IES components. Set-point trajectories are required to meet limits on both production variables (i.e., the variables to be optimized such as the electrical power, the hydrogen production rate, etc.) and process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.). To evaluate the feasibility of HERON generated set-points and to do so in an acceptable time, FARM employs reduced order models to represent the dynamic behavior of the systems to be dispatched. These surrogate models take the form of a linear dynamic system with sets of Linear Parameter Varying (LPV) matrices that are mapped to the system operating space. These matrices are derived from the trajectories of system state variables and system output variables during transients. The accuracy of LPV matrices depends on the selection of state variables. In previous reports, state variables were selected by adopting a complicated workflow requiring multiple software licenses and an advanced level of user expertise. In this report, a new workflow that automates the state variable selection process is presented. It significantly reduces the frequency of user interventions and does not require multiple software licenses. Each module in the new workflow is described in detail, and the input / output examples in each step of the workflow are provided. It was demonstrated that this workflow can greatly reduce the complexity of the state variable selection process, and that the updated FARM-Gamma and FARM-Delta validators can benefit from this workflow when solving the power dispatch problem of a representative IES test case. Finally, some code improvements that can further enhance the efficiency are suggested.

42 ENGINEERING↗
DOE OSTI2012

Testing Dual Rotary Filters - 12373

The Savannah River National Laboratory (SRNL) installed and tested two hydraulically connected SpinTek{sup R} Rotary Micro-filter units to determine the behavior of a multiple filter system and develop a multi-filter automated control scheme. Developing and testing the control of multiple filters was the next step in the development of the rotary filter for deployment. The test stand was assembled using as much of the hardware planned for use in the field including instrumentation and valving. The control scheme developed will serve as the basis for the scheme used in deployment. The multi filter setup was controlled via an Emerson DeltaV control system running version 10.3 software. Emerson model MD controllers were installed to run the control algorithms developed during this test. Savannah River Remediation (SRR) Process Control Engineering personnel developed the software used to operate the process test model. While a variety of control schemes were tested, two primary algorithms provided extremely stable control as well as significant resistance to process upsets that could lead to equipment interlock conditions. The control system was tuned to provide satisfactory response to changing conditions during the operation of the multi-filter system. Stability was maintained through the startup and shutdown of one of the filter units while the second was still in operation. The equipment selected for deployment, including the concentrate discharge control valve, the pressure transmitters, and flow meters, performed well. Automation of the valve control integrated well with the control scheme and when used in concert with the other control variables, allowed automated control of the dual rotary filter system. Experience acquired on a multi-filter system behavior and with the system layout during this test helped to identify areas where the current deployment rotary filter installation design could be improved. Completion of this testing provides the necessary information on the control and system behavior that will be used in deployment on actual waste. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Simplified inelastic constitutive models for ASME Section III, Division 5 design by inelastic analysis

This report describes the development of simplified, universal constitutive model that captures the high temperature monotonic and cyclic behavior of a range of commonly-used high temperature materials. The goal of the work is to provide a simple, universal constitutive model to replace the current bespoke models for Grade 91, 316H, and Alloy 617 included in Nonmandatory Appendix HBB-Z of the ASME Boiler & Pressure Vessel Code, and to extend this model to cover Alloy 800H. We initiated this work in response to feedback from reactor vendors and other Code users requesting simplified models, compared to the current models, that are easier to implement and use in commercial finite element analysis software. This report describes the completion of this effort by developing a model to correct the defects in standard model forms presently used for high temperature material modeling, described in past work, developing and implementing new numerical methods to train this model against test data, and then actually training the model for the four materials. The report provides a complete mathematical description of the model along with the tabulated material coefficients for the four materials. The final step will be to formulate an ASME Code change to introduce the new models into the Code.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Vacuum arc behavior and its voltage characteristics in drawing process controlled by composite magnetic fields along axial and transverse directions

In this research, drawing vacuum arc (VA) experiments were conducted using composite contacts under currents ranging from 5 kA to 20 kA root mean square (rms). The new type of contact comprised an axial magnetic field (AMF) configuration and a transverse magnetic field (TMF) configuration. The TMF plate was in the center, surrounded by the AMF plate. The contact generated both AMFs and TMFs simultaneously. VA appearances and arc voltages were recorded, and the VA was modeled as a conductor for electromagnetic force analysis in ANSYS software. The results showed that the coaxiality of operating mechanisms significantly influenced arc behavior just as the arc was ignited. When arc brightness did not increase after ignition, there was a voltage drop accompanied with diffusion of the VA. As to VA development, when an arc was ignited on an AMF plate, it spread on the plate and rotated. Over time the arc current increased, the constricting arc forms, and the arc column rotated on the TMF plate under the action of Ampere's force. With regard to the influence of a magnetic field on a VA at different stages, in the initial drawing arc stage the TMF was dominant, and the arc started to rotate under the action of Ampere's force. Afterwards, the AMF was dominant, with a steadily burning arc. As for contact melting, in the initial arcing period, a contracted short arc caused severe melting and erosion of the contact plate. When the ignition spot or root was close to the slot of plate, the electromagnetic force pushed the arc toward slot and contact edge, resulting in local erosion of the slot region.

42 ENGINEERING↗
NASA NTRS2015

Online Dectection and Modeling of Safety Boundaries for Aerospace Application Using Bayesian Statistics

The behavior of complex aerospace systems is governed by numerous parameters. For safety analysis it is important to understand how the system behaves with respect to these parameter values. In particular, understanding the boundaries between safe and unsafe regions is of major importance. In this paper, we describe a hierarchical Bayesian statistical modeling approach for the online detection and characterization of such boundaries. Our method for classification with active learning uses a particle filter-based model and a boundary-aware metric for best performance. From a library of candidate shapes incorporated with domain expert knowledge, the location and parameters of the boundaries are estimated using advanced Bayesian modeling techniques. The results of our boundary analysis are then provided in a form understandable by the domain expert. We illustrate our approach using a simulation model of a NASA neuro-adaptive flight control system, as well as a system for the detection of separation violations in the terminal airspace.

Statistics↗
DOE OSTI2014

A comprehensive evaluation of various sensitivity analysis methods: A case study with a hydrological model

Sensitivity analysis (SA) is a commonly used approach for identifying important parameters that dominate model behaviors. We use a newly developed software package, a Problem Solving environment for Uncertainty Analysis and Design Exploration (PSUADE), to evaluate the effectiveness and efficiency of ten widely used SA methods, including seven qualitative and three quantitative ones. All SA methods are tested using a variety of sampling techniques to screen out the most sensitive (i.e., important) parameters from the insensitive ones. The Sacramento Soil Moisture Accounting (SAC-SMA) model, which has thirteen tunable parameters, is used for illustration. The South Branch Potomac River basin near Springfield, West Virginia in the U.S. is chosen as the study area. The key findings from this study are: (1) For qualitative SA methods, Correlation Analysis (CA), Regression Analysis (RA), and Gaussian Process (GP) screening methods are shown to be not effective in this example. Morris One-At-a-Time (MOAT) screening is the most efficient, needing only 280 samples to identify the most important parameters, but it is the least robust method. Multivariate Adaptive Regression Splines (MARS), Delta Test (DT) and Sum-Of-Trees (SOT) screening methods need about 400–600 samples for the same purpose. Monte Carlo (MC), Orthogonal Array (OA) and Orthogonal Array based Latin Hypercube (OALH) are appropriate sampling techniques for them; (2) For quantitative SA methods, at least 2777 samples are needed for Fourier Amplitude Sensitivity Test (FAST) to identity parameter main effect. McKay method needs about 360 samples to evaluate the main effect, more than 1000 samples to assess the two-way interaction effect. OALH and LPτ (LPTAU) sampling techniques are more appropriate for McKay method. For the Sobol' method, the minimum samples needed are 1050 to compute the first-order and total sensitivity indices correctly. These comparisons show that qualitative SA methods are more efficient but less accurate and robust than quantitative ones.

58 GEOSCIENCES↗
DOE OSTI2020

Accelerating Hanford Site Cleanup through Operations Research Modeling - 20238

The Hanford Site cleanup effort will require the integration of dozens of unique facilities and processes, many of which will be first-of-a-kind in implementation and design. Each facility will be governed by its own set of operating logic, configured with a unique array of unit operations, and subject to a set of constraints that will affect its behavior. The collection of facilities have multiple points of interface, making the operations of any one facility potentially significant to the operations of other up- or downstream processes. It is therefore highly desirable to accurately predict these operations, as it allows for Site officials to identify and preempt bottlenecks and vulnerabilities before they unexpectedly inhibit the cleanup mission. With the quantity and complexity of the processes that will be on Site, building a pen-and-paper or even a spreadsheet-assisted model of the cleanup mission quickly becomes overwhelming in scope and inaccurate in execution. The Engineering organization for the Site's Tank Operations Contract (TOC) has therefore implemented the use of operations research (OR) modeling to simulate and predict future operations of Site facilities. These models are created using a discrete event simulation tool that allows for the development of detailed, versatile, and robust models. Not only can these models account for complex logical behaviors, but they can also simulate process details down to the level of vessel sizing, labor utilization, equipment reliability, and resource availability. To date, the TOC has developed OR models for several facilities on Site, including for single-shell tank (SST) farms, double-shell tank (DST) farms, the Effluent Treatment Facility (ETF), and the waste transfer system. These models have focused on identifying bottlenecks and operational constraints, and have been used to quantify the effects of implementing process changes. This latter point is particularly valuable, as it allows for several alternatives to be studied in a virtual setting before committing resources to making a change in the field. The decision to develop OR models has gained tremendous support from the Site's stakeholders and the U.S. Department of Energy (DOE) management, and has prompted the use of the tool to support additional internal and external initiatives. Recently, an initiative was proposed to use the models to help identify and provide quantitative backing for risks and opportunities for the TOC. This application of OR could not only help inform how the TOC manages its risks (e.g. quantities and types of spare parts), but could also help drive process improvements whose benefits might otherwise be hard to quantify. The models have also been used to drive the TOC's cloud computing, artificial intelligence (AI), and machine learning (ML) initiatives. These initiatives will not only improve the ability of the TOC to more rapidly respond to the needs of its customers, but it will also aid in the ability of the TOC to analyze and improve the processes it studies. Partnership with two external software development and consulting companies (Lanner and Ynformed) has furthered not only the application of AI and ML within the TOC, but has also spurred the development of new/improved software tools and platforms used by the companies. These partnerships have proven to be mutually beneficial and productive, and have set a precedent for the types of gains that can be made by exploring such options. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Argonne Reactor Code Software Verification and Validation Plan for the Versatile Test Reactor

This Argonne Reactor Code (ARC) software has taken a pivotal role in the design work of the Versatile Test Reactor. The ARC software itself consists of several independent or semiindependent pieces of software that are used in concert to carry out specific analysis and design objectives. In this report, we discuss the validation that is needed for the ARC software overall and discuss available, usable experimental data and how it relates to the VTR project. We also discuss the verification that is required for the ARC software with respect to its usage in the VTR project and give some concrete examples as to what it must accomplish. A list of goals for the verification and validation work are presented as the general procedure that will be implemented for every individual piece of software in ARC. The ARC software has been continuously developed for over 50 years and many of the features used for the VTR project have thus been rigorously tested for accuracy during that timeframe. The ARC software is presently under source code control and undergoes nightly regression testing of not only the individual pieces, but the interconnected aspects that are common to most analysis projects. Its greatest weakness, from a software verification and validation perspective, is both a lack of documentation and outdated documentation. As an example, much of the previous validation work will require contemporary effort to re-evaluate given the updated base data libraries and modifications to the software that have occurred since. This requires new documentation to be produced to support the usage of the software in the VTR project. The bulk of the ARC software is focused on steady state neutronics and TH behavior of a reactor system. In this regard, we have identified the ZPPR, FFTF, and EBR-II programs as the best candidates for sources of validation data for the VTR project. The ZPPR-15 series in the ZPPR program was chosen as it is the best representation of the VTR fuel form and reactor core layout of all of the ZPPR measurements. Additional support for it comes from the fact that most of the data has already been processed into usable ARC models for VTR validation. The FFTF and EBR-II reactors were both functional reactors that provide reactor scale measurements. FFTF is clearly a closer match to VTR and its startup measurements would be a very valuable validation basis. EBR-II has invaluable burnup related measurements that will play a key role in the ARC software validation work. Each piece of ARC software will require a report detailing the software verification. The validation work will be logically split into the results of modeling each identified experimental resource (ZPPR, EBR-II, FFTF). The intended timeline for the VTR project is to have the ARC software verified and validated by the end of fiscal year 2020. This is incumbent on sufficient funding allocated to V&V activities and no change in programmatic priorities.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1992

An experimental methodology for a fuzzy set preference model

A flexible fuzzy set preference model first requires approximate methodologies for implementation. Fuzzy sets must be defined for each individual consumer using computer software, requiring a minimum of time and expertise on the part of the consumer. The amount of information needed in defining sets must also be established. The model itself must adapt fully to the subject's choice of attributes (vague or precise), attribute levels, and importance weights. The resulting individual-level model should be fully adapted to each consumer. The methodologies needed to develop this model will be equally useful in a new generation of intelligent systems which interact with ordinary consumers, controlling electronic devices through fuzzy expert systems or making recommendations based on a variety of inputs. The power of personal computers and their acceptance by consumers has yet to be fully utilized to create interactive knowledge systems that fully adapt their function to the user. Understanding individual consumer preferences is critical to the design of new products and the estimation of demand (market share) for existing products, which in turn is an input to management systems concerned with production and distribution. The question of what to make, for whom to make it and how much to make requires an understanding of the customer's preferences and the trade-offs that exist between alternatives. Conjoint analysis is a widely used methodology which de-composes an overall preference for an object into a combination of preferences for its constituent parts (attributes such as taste and price), which are combined using an appropriate combination function. Preferences are often expressed using linguistic terms which cannot be represented in conjoint models. Current models are also not implemented an individual level, making it difficult to reach meaningful conclusions about the cause of an individual's behavior from an aggregate model. The combination of complex aggregate models and vague linguistic preferences has greatly limited the usefulness and predictive validity of existing preference models. A fuzzy set preference model that uses linguistic variables and a fully interactive implementation should be able to simultaneously address these issues and substantially improve the accuracy of demand estimates. The parallel implementation of crisp and fuzzy conjoint models using identical data not only validates the fuzzy set model but also provides an opportunity to assess the impact of fuzzy set definitions and individual attribute choices implemented in the interactive methodology developed in this research. The generalized experimental tools needed for conjoint models can also be applied to many other types of intelligent systems.

Turksen, I. B.↗
DOE OSTI2019

Experimental Investigation on Metallic Droplet Behavior in Molten BOF Slag

In order to better understand the metallic droplet behavior during a slag treatment process, a physical modeling based on the similarity principle was performed in a transparent scaled-down vessel at room temperature. Paraffin oil, 20 wt pct copper sulfate solution, and compressed air were used to simulate the molten slag, metallic droplet, and carrier gas, respectively. The droplets injected into paraffin oil during the experiment were captured by a high speed camera and were analyzed by Image Pro Plus software to obtain the droplet size distribution. The critical droplet size in the physical modeling and slag treatment process is quantitatively correlated. The results show that droplet breakage phenomenon is dominant over its coalescence in the current industrial practice, and droplet breakage is enhanced with increasing gas flow rate and/or lance depth. No significant effect of the nozzle configuration was found on the droplet breakage and coalescence. The droplet size distribution varies with the lance position. Gas flow rate and lance depth are the most important factors for droplet breakage, the extent of which can be reduced through a proper selection of the operational conditions. A linear relationship between the droplet size and the input energy flux is obtained.

36 MATERIALS SCIENCE↗
DOE OSTI2015

SU-C-210-07: Assessment of Intra-/Inter-Fractional Internal Tumor and Organ Movement in Radiotherapy of Head and Neck Cancer Using On-Board Cine MRI

Purpose: Head and neck (H&N) internal organ motion has previously been determined with low frequency and temporary nature based on population-based pre- and post-treatment studies. Using immobilization masks and adding a 4–6 mm planning-tumor-volume margin, geometric uncertainties of patients are routinely considered clinically inconsequential in H&N radiotherapy. Using the first commercially-available MR-IGRT system, we conducted the first quantitative study on inter-patient, intra- and inter-fractional H&N internal motion patterns to evaluate the necessity of individualized asymmetric internal margins. Methods: Ninety cine sagittal MR image sequences were acquired during the entire treatment course (6–7 weeks) of three H&N cancer patients using the ViewRay™ MR-IGRT system. The images were 5 mm thick and acquired at 4 frames/per second. One of the patients had a tracheostomy tube. The cross-sectional H&N airway (nasopharynx, oropharynx, and laryngopharynx portions) movement was analyzed comprehensively using in-house developed motion detection software. Results: Large inter-patient variations of swallowing frequency (0–1 times/per fraction), swallowing duration (1–3 seconds), and pharyngeal cross-sectional area (238–2516 mm2) were observed. Extensive pharyngeal motion occurred during swallowing, while nonzero and periodic change of airway geometry was observed in resting. For patient 1 with tracheostomy tube replacement, 30.3%, 30.0%, 48.7% and 0.3% of total frames showed ≥ 4 mm displacements in the anterior, posterior, inferior, and superior airway boundaries, respectively; similarly, (5.7%, 0.0%, 0.0%, 0.3%) and (23.3%, 0.0%, 35.7%, 1.7%) occurred for patients 2 and 3. Area overlapping coefficients with respect to the first frame were 76.3+/−6.4%, 90.3+/−0.6%, and 92.3+/−1.2% for the three patients, respectively. Conclusion: Both the resting and swallowing motions varied in frequency and amplitude among the patients and across fractions of a patient’s treatment. Patients receiving surgery that alters their respiratory and swallowing behavior can have significant intra-fractional internal motion. Patient-specific organ/tumor motion analysis may yield individualized asymmetric internal margins and improve the therapeutic ratio.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Insert Modeling in UNF ST&DARDS

The Used Nuclear Fuel-Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS) is a software tool that integrates a used nuclear fuel (UNF) or spent nuclear fuel (SNF) relational database and key analysis capabilities to simplify and automate numerous UNF management and fuel cycle–related activities. UNF-ST&DARDS is being developed for the US Department of Energy’s Office of Nuclear Energy Spent Fuel and Waste Disposition program. UNF-ST&DARDS provides an integrated framework that uses advanced modeling and simulation to predict the behavior of SNF over the timescales associated with permanent disposal in a geologic repository. After leaving the spent fuel pool, SNF is transferred to dry storage in a dual-purpose canister (DPC). DPCs are considered “dual purpose” because they are designed for both storage and transportation, removing the need to transfer the fuel to a separate transportation cask. However, much research has been conducted investigating the feasibility of directly disposing of DPCs in geologic repositories. Direct disposal of DPCs could reduce worker exposure during repackaging, reducing the amount of low-level waste from the discarded DPCs and potentially saving billions of dollars. Therefore, direct disposal of as-loaded DPCs is desirable if it can be done safely.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗