Additive manufacturing of soft magnets for electrical machines—a review
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36 MATERIALS SCIENCE↗
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Fast Iterative Multi-site Hosting Capacity Analysis for Distribution Systems With Search Space Pruning
Interconnection studies for distributed energy resources (DERs) is a time-intensive process, primarily due to the necessity of solving large number of power flow scenarios. Hosting capacity analysis (HCA) is a time-consuming aspect of interconnection studies that is divided into single-site HCA (SHCA) and multi-site HCA (MHCA). From a computational and understandable standpoint, the industry seeks iteration-based solutions for SHCA, although it doesn't maximize the total DER hosting capacity (DERHC) of the grid, as MHCA does. While non-iterative solutions are available for MHCA, they involve a trade-off between the modeling accuracy of the distribution system, solution quality, and ease of understanding. In this work, we present a fast iterative solution for MHCA, reducing computational complexity by eliminating the need to solve power flows for a large amount of search space, thus making iterative solutions feasible. This iterative approach guarantees both a global optimal solution with sufficient time and a fast, close-to-optimal solution through efficient search space pruning. It also easily integrates with existing utility HCA tools. The results are demonstrated on select locations in the IEEE-123 bus system for community-scale interconnection studies. We highlight the benefits of skipping the need to solve millions of power flows, all while maximizing the grid's total DERHC.
Guddanti, Kishan Prudhvi↗
Probabilistic Study Conducted on Sensor-Based Engine Life Calculation
Turbine engine life management is a very complicated process to ensure the safe operation of an engine subjected to complex usage. The challenge of life management is to find a reasonable compromise between the safe operation and the maximum usage of critical parts to reduce maintenance costs. The commonly used "cycle count" approach does not take the engine operation conditions into account, and it oversimplifies the calculation of the life usage. Because of the shortcomings, many engine components are regularly pulled for maintenance before their usable life is over. And, if an engine has been running regularly under more severe conditions, components might not be taken out of service before they exceed their designed risk of failure. The NASA Glenn Research Center and its industrial and academic partners have been using measurable parameters to improve engine life estimation. This study was based on the Monte Carlo simulation of 5000 typical flights under various operating conditions. First a closed-loop engine model was developed to simulate the engine operation across the mission profile and a thermomechanical fatigue (TMF) damage model was used to calculate the actual damage during takeoff, where the maximum TMF accumulates. Next, a Weibull distribution was used to estimate the implied probability of failure for a given accumulated cycle count. Monte Carlo simulations were then employed to find the profiles of the TMF damage under different operating assumptions including parameter uncertainties. Finally, probabilities of failure for different operating conditions were analyzed to demonstrate the importance of a sensor-based damage calculation in order to better manage the risk of failure and on-wing life.
Guo, Ten-Huei↗
Computation of Reacting Flows in Combustion Processes
The main objective of this research was to develop an efficient three-dimensional computer code for chemically reacting flows. The main computer code developed is ALLSPD-3D. The ALLSPD-3D computer program is developed for the calculation of three-dimensional, chemically reacting flows with sprays. The ALL-SPD code employs a coupled, strongly implicit solution procedure for turbulent spray combustion flows. A stochastic droplet model and an efficient method for treatment of the spray source terms in the gas-phase equations are used to calculate the evaporating liquid sprays. The chemistry treatment in the code is general enough that an arbitrary number of reaction and species can be defined by the users. Also, it is written in generalized curvilinear coordinates with both multi-block and flexible internal blockage capabilities to handle complex geometries. In addition, for general industrial combustion applications, the code provides both dilution and transpiration cooling capabilities. The ALLSPD algorithm, which employs the preconditioning and eigenvalue rescaling techniques, is capable of providing efficient solution for flows with a wide range of Mach numbers. Although written for three-dimensional flows in general, the code can be used for two-dimensional and axisymmetric flow computations as well. The code is written in such a way that it can be run in various computer platforms (supercomputers, workstations and parallel processors) and the GUI (Graphical User Interface) should provide a user-friendly tool in setting up and running the code.
Keith, Theo G., Jr.↗
Modeling the self-assembly of ordered nanoporous materials
This report describes progress on a collaborative project on the multiscale modeling of the assembly processes in the synthesis of nanoporous materials. Such materials are of enormous importance in modern technology with application in the chemical process industries, biomedicine and biotechnology as well as microelectronics. The project focuses on two important classes of materials: i) microporous crystalline materials, such as zeolites, and ii) ordered mesoporous materials. In the first case the pores are part of the crystalline structure, while in the second the structures are amorphous on the atomistic length scale but where surfactant templating gives rise to order on the length scale of 2 - 20 nm. We have developed a modeling framework that encompasses both these kinds of materials. Our models focus on the assembly of corner sharing silica tetrahedra in the presence of structure directing agents. We emphasize a balance between sufficient realism in the models and computational tractibility given the complex many-body phenomena. We use both on-lattice and off-lattice models and the primary computational tools are Monte Carlo simulations with sampling techniques and ensembles appropriate to specific situations. Our modeling approach is the first to capture silica polymerization, nanopore crystallization, and mesopore formation through computer-simulated self assembly.
36 MATERIALS SCIENCE↗
Design of Hypervelocity Flow Generator (HFG) and Its Diagnostics
Ground facilities for hypersonic research are a key element for successful development of aerodynamically proven hypervelocity vehicles. Design concepts and diagnostics of a hypervelocity flow generator (HFG) were made as a test platform for hypersonic/hypervelocity spacecraft models at the NASA Langley Research Center. The HFG is a hypersonic flow field generator using optically heated gas which is blown into an 80 cu m vacuum chamber. The vacuum chamber is kept at a stable vacuum pressure with a combination of three large vacuum pumps, while the HFG is in the test mode. The HFG provides a relatively small test section with approximately a 20 cm window. This facility was designed to generate 2.45 km/sec of flow speed, and potentially generate a continuous flow with the nozzle and vacuum system. The window in test section provides a direct view of the shock wave around a model in order to measure temperature, pressure, and density profile within the shock layer. One of the key test goals under this project is to understand why the emission spectra from the standing shockwave plasma predicted by Lora-Loran codes are significantly different from the measured emission spectra from the Flight Investigation Reentry Environment (FIRE II) Flight. The correct estimate of the thermal loading on the leading edge of hypersonic vehicles greatly affects the aerodynamic design, the material selection for the vehicle, and the cooling requirement and can be obtained by the precise modeling of emission spectra from shockwave plasma. However, the estimation of thermal loading is not an easy task due to complex non-equilibrium radiative process within high temperature shock layers that still falls into a category of cold plasma. Direct flight experiments are the most desirable, but not a cost-effective approach. Analysis by computational fluid dynamics (CFD) offers many test flexibilities. However, the CFD codes must be fully tested and validated with experimental data before the codes are effectively used for practical design. Large discrepancies between experiments and codes appear in hypersonic/hypervelocity flow regimes at high altitudes of 60 km ~ 90 km. This HFG facility offers some important parameters for CFD code validation, such as collision cross-sections, relaxation times, reaction rate coefficients and transportation coefficients. The HFG test facility is based on the ejection flow of high temperature gas heated over to 3500 K through a nozzle. The tungsten gas chamber of the HFG is heated up to a desired temperature by a 60 kW optical power beam source. This system consists of an optical power source, a thermal chamber, an expansion nozzle, a test section, and an 80 cu m vacuum tank. 60 kW optical input power is obtained from the 150 kW Vortek arc lamp system (by Vortek Industries, Vancouver, Canada). This optical beam is focused to heat the gas chamber within which a flow media is heated. The maximum achievable temperature of the flow medium reached approximately 3500 K or even higher but is limited by the melting point of the chamber material used. The exhaust velocity through the nozzle was determined by the stagnation temperature and the molecular weight of the working medium at the test section. To provide design parameters, a NASA Chemical Equilibrium with Application (CEA) computer program is used for the simulation of aerothermal data. This CEA program can calculate chemical equilibrium and properties of complex mixtures using shock tube parameters. For nitrogen gas at 2666 K stagnation temperature, the maximum achievable velocity at the test section is approximately 2.45 km/sec which is within the range of the thermal velocity of 8000 K shock layer. Based on the calculation through the CEA program, the design parameters of a HFG were determined and implemented for the test section that includes an expansion nozzle. The installed test section of the experimental facility can sustain a condition of a re-entry vehicle from the Space at an altitude of 60-90 km. After installation of the HFG, the system was fully tested and its operational parameters were measured. An 80 cu m vacuum chamber of HFG was set at 1 torr level to keep a stable downstream condition. The pumping time to reach the minimum vacuum pressure (~ 1 torr) at the test chamber from atmospheric pressure was approximately an hour using Kinney (MBV-14000/MB -1600/KT-300) and Stokes (Model 1772 and 412) pumps. Such a setup condition allowed a continued stable operation of the HFG experiment with flowrates through 1-, 3-, or 5-mm diameters of nozzle throat. The flow characteristics of the HFG for various operating conditions were performed using a focused Schlieren method. At 0.8 torr chamber pressure, a barrel shock was observed at the test section. With a sphere obstacle of 12 mm diameter in the flow, a bow shock (~ 2-mm thickness) was observed by a focused Schlieren visualization method.
Hypervelocity flow↗
High-Speed Friction Stir Welding of AA7075-T6 Sheet: Microstructure, Mechanical Properties, Micro-texture, and Thermal History
Friction-stir-welding (FSW) is a cost-effective and high quality joining process for aluminum alloys (especially heat-treatable allo ys) that has been applied successfully in the aerospace industry. However, the full potential of FSW on more cost-sensitive applications is still limited by the production rate, namely the welding speed of the process. The majority of literature evaluating FSW of aluminum alloys is based on welds made in the range of welding speeds around hundreds of millimeters per minute, and only a handful are at a moderate speed of 1 m/min. In this study we present a microstructural analysis of friction stir welded AA7075-T6 blanks with welding speeds up to 3 m/min. Textures, microstructures, mechanical properties, and weld quality are analyzed using TEM, EBSD, metallographic imaging, and Vickers hardness. Results are coupled with welding parameters to aid in the understanding of the complex material flow and texture gradients within the welds in an effort to optimize welding parameters for high speed processing.
Zhang, Jingyi↗
Deposition of tungsten metal by an immersion process
A new multi-step, solution-phase method for the spontaneous deposition of tungsten from a room temperature ethereal solution is reported. This immersion process relies on the deposition of a sacrificial zinc coating which is galvanically displaced by the ether-mediated reduction of oxophilic WCl 6 . Subsequent thermal treatment renders a crystalline, metallic tungsten film. The chemical evolution of the surface and formation of a complex intermediate tungsten species is characterized by X-ray diffraction, infrared spectroscopy, and X-ray photoelectron spectroscopy. Efficient metallic tungsten deposition is first characterized on a graphite substrate and then demonstrated on a functional carbon foam electrode. The resulting electrochemical performance of the modified electrode is interrogated with the canonical aqueous ferricyanide system. A tungsten-coated carbon foam electrode showed that both electrode resistance and overall electrochemical cell resistance were reduced by 50%, resulting in a concomitant decrease in redox peak separation from 1.902 V to 0.783 V. Furthermore, this process promises voltage efficiency gains in electrodes for energy storage technologies and demonstrates the viability of a new route to tungsten coating for technologies and industries where high conductivity and chemical stability are paramount.
36 MATERIALS SCIENCE↗
Precision Casting via Advanced Simulation and Manufacturing
A two-year program was conducted to develop and commercially implement selected casting manufacturing technologies to enable significant reductions in the costs of castings, increase the complexity and dimensional accuracy of castings, and reduce the development times for delivery of high quality castings. The industry-led R&D project was cost shared with NASA's Aerospace Industry Technology Program (AITP). The Rocketdyne Division of Boeing North American, Inc. served as the team lead with participation from Lockheed Martin, Ford Motor Company, Howmet Corporation, PCC Airfoils, General Electric, UES, Inc., University of Alabama, Auburn University, Robinson, Inc., Aracor, and NASA-LeRC. The technical effort was organized into four distinct tasks. The accomplishments reported herein. Task 1.0 developed advanced simulation technology for core molding. Ford headed up this task. On this program, a specialized core machine was designed and built. Task 2.0 focused on intelligent process control for precision core molding. Howmet led this effort. The primary focus of these experimental efforts was to characterize the process parameters that have a strong impact on dimensional control issues of injection molded cores during their fabrication. Task 3.0 developed and applied rapid prototyping to produce near net shape castings. Rocketdyne was responsible for this task. CAD files were generated using reverse engineering, rapid prototype patterns were fabricated using SLS and SLA, and castings produced and evaluated. Task 4.0 was aimed at developing technology transfer. Rocketdyne coordinated this task. Casting related technology, explored and evaluated in the first three tasks of this program, was implemented into manufacturing processes.
Source record↗
Additive Manufacturing: The Rise of a Technology and the Need for Quality Control and Inspection Techniques
Additive manufacturing (AM) technology, also known as three-dimensional (3D) printing, rapid prototyping (RP), or solid free forms (SFF), was developed back in the early 1980s. The technology was quickly commercialized in the late 1980s, and since then, the technology has been widely used in different applications at several industrial sectors. AM offers distinct advantages from traditional, subtractive manufacturing techniques. Traditional subtractive manufacturing techniques, including milling, drilling, and turning, are techniques that start with a large block of stock material, which is then subtracted from until the final desired product is reached, leaving much of the initial block as wasted scrap. In the AM process, the part is constructed by depositing material layer by layer in the Z-direction until the final product is produced, leaving little to no waste. The process starts with a computer-aided design (CAD) model that gets sliced into individual layers using software that generates instructions, known as G-code, which are sent to the AM machine. Here, this process allows complex geometry construction that traditional methods would have diffi-culty accomplishing or fail completely. In some cases, a secondary finishing process is needed such as polishing, sintering, curing, sanding, powder removal, or painting.
36 MATERIALS SCIENCE↗
A Coacervate-Based Mixed-Conducting Binder for High-Power, High-Energy Batteries
Polymer binders add crucial structural integrity to lithium ion battery composite cathodes, but industry standard binders, such as polyvinylidene fluoride (PVDF), are insulating to ions and electrons, detrimentally adding resistance to the overall system. In this work, we use electrostatics to stabilize a blend of a charged conjugated polymer with an oppositely charged polyelectrolyte, providing a processable, stable binder with high ionic and electronic conduction. Using LiFePO4 cathodes as a model system, we show significant improvement in rate capability and stability, with the conducting binder enabling a 39% utilization at 6C compared to 1.6% when PVDF is the binder. Additionally, the conducting binder affords a 63% capacity retention over 400 C/2 cycles, compared to only a 6% retention over 400 cycles when PVDF is the binder. These results show that electrostatically stabilized complexation is a promising strategy to integrate both electronic and ionic conductivity into a binder, while simultaneously maintaining stability and processability.
36 MATERIALS SCIENCE↗
Impact of surface hydrophilicity on the ordering and transport properties of bicontinuous microemulsions
Microemulsions (MEs) have many industrial applications, where recent developments have shown that MEs can be utilized for electrochemical applications, including potentially in redox flow batteries. However, understanding the structure and dynamics of these systems, including at a surface, is needed to direct and rationally control their electrochemical behavior. While bulk solution measurements have provided insight into their structure, their assembly at an interface also impacts the electron (to the electrode) and ion (across the surfactant) charge transfer processes in the system. To address this shortcoming, neutron reflectivity experiments and molecular simulations have been completed that document the near surface structure of a series of deuterated water (D 2 O)/polysorbate-20/toluene MEs on hydrophilic and amphiphilic surfaces. These results show that the microemulsions form complex layered structures near a hard electrode surface, where most layers are not purely one component. Decreasing the D 2 O concentration in the ME increases the number of and purity of the layers established on the solid surface. These lamellar-type layers transition from the surface to the bulk microemulsion as a series of mixed layers (i.e., containing oil, water, and surfactant) that are consistent with perforated lamellae. Additionally, these mixed lamellae appear to become more perforated with oil and water pathways on an amphiphilic surface. Furthermore, the purity and thickness of these layers will influence the accessibility of an electrode by redox active species, as well as ion transport required to satisfy the electroneutrality condition.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Knowledge Spillovers and Cost Reductions in Solar Soft Costs
Despite the commonly acknowledged importance of knowledge spillovers in reducing solar soft costs, we are only beginning to answer a fundamental question: who learns what (knowledge acquisition), from whom (knowledge production), and how (spillover mechanisms)? Until recently, this important topic has been largely unexplored in the case of solar soft costs. Thus, this project set out to identify how knowledge spillovers affect soft costs in the U.S. photovoltaic (PV) installation industry, specifically how important spillovers are, what types of knowledge are most likely to spillover, and how networks of actors affect spillovers. Our findings offer insights for designing solutions that address problems associated with knowledge spillovers and that leverage spillovers to reduce solar soft costs. Recognizing the ambiguity in the definition of soft costs, i.e., “non-hardware costs,” and variability in soft cost categories, we developed the Solar Soft Cost Ontology (SSCO) to systematically identify key concepts related to soft costs, network actors, learning processes, and the relationships between them. This ontology served as a foundational organizational structure for the methodology of the remaining tasks: case studies, surveys, pricing analysis, patent analysis, network analysis, and project integration across tasks. While there is substantial learning among installers that is reducing the soft costs for PV installations, most of that learning is retained by firms rather than spread across the industry. The positive relationship between experience accumulation and cost reductions is typically explained as learning by doing (LBD), but we find that LBD effects are mediated by other learning mechanisms, including learning by searching and learning by interacting. Knowledge spillovers have significant potential to reduce solar PV soft costs, but successful knowledge spillover pathways are complex and non-trivial. There are a wide variety of ways to construct an installation business, thus categories of firms that can effectively cross-learn directly are small and what knowledge is relevant to whom is challenging and costly for firms to assess. This fragmentation limits the critical mass needed for spillover related soft cost reductions. Knowledge does not flow directly between installers. Indirect knowledge transfer pathways are critical: distributors, software providers, collaboratives, and hiring. Furthermore, diverse, more integrated knowledge networks tend to promote successful learning by organizations and across the system as a whole. Accordingly, we find the need to supporting the whole ecosystem using an integrated policy and programmatic approach to support installers, distributors, complementary sector, and facilitators. Overall, a deliberate policy-mix design is needed to reduce the solar PV deployment barrier in terms of installation cost reductions, because deployment policies could potentially interact with policies that facilitate network-building and technological innovation. A combination of deployment policies, innovation-support policies, and network-facilitating policies could potentially lead to a more desired market outcome through achieving higher joint learning rates from firms’ cumulative experiences developed in a more integrated production and deployment ecosystem.
14 SOLAR ENERGY↗
Bridging the gap: adapting advanced display technologies for use in hybrid control rooms
The Institute for Energy Technology (IFE), runs the OECD Halden Reactor Project (HRP), featuring a state-of-the-art research simulator facility in Halden, Norway, called HAMMLAB. HAMMLAB serves two main purposes: the study of human behaviour in interaction with complex process systems; and the development, test and evaluation of prototype control centres and their individual systems. By studying operator performance in HAMMLAB and integrating the knowledge gained into new designs, the HRP contributes to improving operational safety, reliability, efficiency and productivity. The U.S. Department of Energy’s (DOE) Light Water Reactor Sustainability (LWRS) Program has contracted IFE to assist DOE national laboratory staff at Idaho National Laboratory (INL) in adapting HAMMLAB design concepts for the purpose of control room modernization at nuclear power plants in the U.S. In support of this effort, the DOE has built a simulator research facility at INL called the Human Systems Simulation Laboratory (HSSL). The HSSL is centered on control room modernization, in which industry provided plant instrumentation and controls are modified for upgrade opportunities. The HSSL houses the LWRS simulator, which is a reconfigurable full-scale and full-scope control room simulator. Consisting of 45 large touchscreens on 15 panels, the LWRS simulator is currently using this glass top technology to digitally represent and replicate the functionality of the analog I&C systems in existing control rooms. The LWRS simulator is reconfigurable in that different plant training simulator models obtained from the utilities can be run on the panels, and the panels can be physically moved and arranged to mimic the layout of those control rooms. The glass top technology and reconfigurability capabilities allow the LWRS simulator to be the research platform that is necessary to design, prototype, and validate human-system interface (HSI) technologies that can replace existing analog I&C. IFE has recently assisted INL in establishing the technical infrastructure for implementation of HSI prototypes from HAMMLAB into the HSSL to demonstrate relevant control room replacement systems in support of the LWRS program. In March, 2014, IFE delivered the first HSI prototype utilizing this infrastructure — a large screen overview display for INL's simulator. The co-operation now continues by developing Procedure Support Displays targeted for operators in hybrid control room settings. These prototypes are being validated with U.S. reactor operators in the HSSL and optimized to enhance their performance. This research serves as a crucial stepping stone toward incorporation of advanced display technologies into conventional main control rooms.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Deconstructing the Nuclear Supply Chain Cyber-Attack Surface
The nuclear supply chain cyber-attack surface is a large, complex network of interconnected stakeholders and activities. The global economy has widened and deepened the supply chain resulting in larger numbers of geographically dispersed locations and increased difficulty ensuring the authenticity and security of digital assets. Although the nuclear industry has made significant strides in securing facilities from cyber-attacks, the supply chain remains vulnerable. This paper provides further details on each of the elements in the Digital I&C System Supply Chain Cyber-Attack Surface, including supply chain lifecycle activities, key stakeholders, touchpoints, and attack types. Deconstructing this attack surface provides insights into supply chain threats, vulnerabilities, and consequences. These insights will lead to improvements in cybersecurity supply chain risk analysis, development of new cybersecurity supply chain processes and tools, and enhancement of overall supply chain resilience.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Scalable Hot-Water-Repellent Superhydrophobicity via Thermal Insulation
Superhydrophobic surfaces, which rely on a combination of surface texture and chemistry, often lose their repellent behavior when contacted by hot water (≳40 °C) because the impinging hot water replaces the requisite air layer within the surface texture via evaporation and recondensation. In contrast to previous approaches targeting this condensation-induced failure mode that rely on intricately tailored surface structures or complex chemical treatments, we present a scalable approach based on thermal design: the multilayered insulated superhydrophobic (MISH) coating mitigates condensation-induced failure by preventing heat transfer. Superhydrophobicity is retained at impinging water temperatures up to 90 °C, with durability demonstrated via long-term (>1 million impacts) droplet impingement experiments. We explain the mechanism for this approach with a detailed thermal model; the model reveals that the underlying physical behavior is self-similar across coating parameters and impinging fluid temperatures. Finally, the MISH coating accommodates curved geometries and large surfaces, and it is over 4 orders of magnitude less expensive than cleanroomnanofabricated alternatives, indicating promise for practical use in the energy sector, chemical processing, and the food and medical industries.
coating materials↗
Predictive LES Modeling and Validation of High-Pressure Turbulent Flames and Flashback in Hydrogen-enriched Gas Turbines
The overall objective of this project is to make advances in large-eddy simulation modeling of swirl-flame flashback at elevated pressure, where the reactants can be premixed or stratified, and composed of methane enriched with hydrogen. The modeling effort was conducted with a companion experimental validation effort that focused on high-speed measurements of flashback in a model swirl-flame combustor. The modeling effort focused on the development of manifold-based combustion model for flashback simulations. The main complexity in this configuration comes from the flames’ propagation through a stratified fuel-air mixture along with heat loss near the walls. For this purpose, a non-adiabatic flamelet model was developed and tested using canonical flow configurations. Further, extensive validation in premixed configurations is used to establish the model’s accuracy in capturing heat loss and flame propagation. Finally, the model was tested using the UT flame flashback experiment, and was shown to accurately capture the flame flashback process. The end products from this work are a) a full validated flameout-based approach for modeling flame flashback; b) a complete implementation of the model in the open source OpenFOAM framework, which has been made available to both industry and academia; c) an extensive suite of validation studies performed using the OpenFOAM solver. In addition, new techniques for flame modeling, subfilter modeling of scalars, and simulation of low Mach number flows were developed and tested. In the experimental validation effort, flashback was studied in a premixed and stratified swirl flame by using high-speed imaging diagnostics. Fuels tested included CH 4 enriched with H 2 , with H 2 enrichment up to 84% by volume. These flashback experiments are conducted at pressures ranging from 1 to 5 atm. A swirler-based fuel-injection system was used to create the fuel-air stratification in the radial direction. For the high-pressure measurements, an optically accessible elevated pressure chamber was used. The spatial distribution of the equivalence ratio under non-reacting conditions was characterized using planar laser-induced fluorescence with acetone as the fuel tracer. It was observed that fuel-air pockets were distributed across the mixing tube width, although in an average sense, the fuel-air mixture was radially stratified. The global behavior of upstream flame propagation was investigated for different levels of hydrogen-enrichment. For stratified hydrogen-rich flashback, the propagation path of the flame changed from the inner wall to outer wall, which was induced by the faster chemistry of stoichiometric mixtures that are frequently present near the outer wall. This behavior of hydrogen-rich flashback persists even at elevated pressures up to 5 atm, although the propagation of the flame occurs as a wide flame tongue as opposed to the acute-tipped flame structures present in the atmospheric cases. The end product of the experimental effort is greatly improved knowledge of flashback physics and a unique database that can be used for model validation.
08 HYDROGEN↗
Solutions for Enhanced Legacy Probabilistic Risk Assessment Tools and Methodologies: Improving Efficiency of Model Development and Processing via Innovative Human Reliability Dependency Analysis
Probabilistic risk assessments (PRAs) are integral to nuclear power plant (NPP) operations, having tremendously benefitted the safety of the U.S. reactor fleet for decades. Insights obtained from the models have provided perspectives on a variety of applications, both at the plant and for the regulator. While these models are very useful, they are now being asked to represent and analyze aspects of the plant that were never envisioned by the initial PRA practitioners. Furthermore, heightened demands on the PRA models have led to increased computing power requirements. Additionally, as the complexity of the PRA models increased, the difficulty experienced by non-PRA experts in trying to understand these models, grasp the insights they provide, and effectively use that information has become problematic. The need for research to address key issues regarding PRA tools and methods has never been greater. Although the nuclear power industry has largely been well-served by these tools and methods, the underlying science is dated, remaining mostly unchanged for over two decades. Three areas were identified as most beneficial to address to maintain and improve the usefulness of the current practice legacy PRA tools: improved quantification speed, increased ability to efficiently model multi-hazard models, and improved modeling human action dependency in PRA. This report is focused on the third critical area, improvements in dependency analysis of human actions conducted as part of a typical human reliability assessment.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗