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DOE OSTI2018

Recurrent Neural Network Language Models for Open Vocabulary Event-Level Cyber Anomaly Detection

Automated analysis methods are crucial aids for monitoring and defending a network to protect the sensitive or confidential data it hosts. This work introduces a flexible, powerful, and unsupervised approach to detecting anomalous behavior in computer and network logs; one that largely eliminates domain-dependent feature engineering employed by existing methods. By treating system logs as threads of interleaved ``sentences'' (event log lines) to train online unsupervised neural network language models, our approach provides an adaptive model of normal network behavior. We compare the effectiveness of both standard and bidirectional recurrent neural network language models at detecting malicious activity within network log data. Extending these models, we introduce a tiered recurrent architecture, which provides context by modeling sequences of users' actions over time. Compared to isolation forests and Principal Components Analysis (PCA), two popular anomaly detection algorithms, we observe superior performance on the Los Alamos National Laboratory Cyber Security dataset. For log-line-level predictions, our best performing character-based model provides test set anomaly scores ranking red team events in the 98th percentile on average, and yields 0.97 area under the receiver operator characteristic curve, demonstrating the strong fine-grained anomaly detection performance of this approach on open vocabulary logging sources.

Cyber Analysis, Deep Learning, language analysis, ↗

DOE OSTI2019

Simulation of Spent Nuclear Fuel loading into a Final Waste Repository

Previous work towards studying repository loading have used: - spent nuclear fuel (SNF) with an average burnup composition; - a lumped capacitance thermal model for calculating temperature in a Cyclus repository model. The goal of this work is to improve on the repository models and use U.S. historical SNF inventory data in simulations to more accurately study the loading of a waste repository. These goals will be achieved by: - using UNF-ST-and-DARDS Unified Database (UDB) that has historic assembly-specific data (e.g, isotopic composition, heat) in Cyclus simulations; - implementing a more accurate thermal model within a Cyclus repository model. Objectives: - Create a Cyclus spent fuel conditioning model that packages spent fuel bundles into packages which have user-defined properties. - Create a Cyclus medium-fidelity repository model that gives accurate time and spatial dependent temperature values and loads the repository based on a user-selected loading strategy. Cyclus is an agent-based extensible framework for modeling flow of material through user-defined nuclear fuel cycles. In Cyclus, each facility in the fuel cycle is modeled individually and the facilities interact with one another as independent agents. The spent fuel conditioning model accepts spent fuel bundles and puts them into a cylindrical waste package. In the spent fuel conditioning model, the user can define variables: For each layer, radius, thermal conductivity, thermal diffusivity; For each package, Number of spent fuel bundles, Radius and height. The waste repository model accepts waste packages and emplaces them into available positions within the waste repository based on a thermal criteria. The thermal criteria is a temperature limit at the interface between the waste package surface and the host geology, that is set based on the repository's host geology. In the waste repository model, the user can define the variables: Capacity, Distance between waste packages, Distance between drifts, Repository host geology, Loading Strategy. After the addition of new waste packages at each time step, the waste repository model recalculates the temperature at each location in the repository. If the addition of this new package causes its temperature to exceed the thermal limit, it will be placed back into the buffer. A thermal model that relies on a transient 'outside' model and quasi-steady-state 'inside' model is used to accurately determine the temperature in the repository. The 'outside' model assumes a homogenous medium with the Engineered Barrier System (EBS) replaced by the geologic medium. Temperature solutions for the central waste package, adjacent point and line sources are superimposed to calculate the temperature at specific points in the repository. The central drift consists of one finite line source which represents the central waste package. The central drift also consists of point sources that represent neighboring waste packages in the central drift. The neighboring drifts are represented by infinite line sources. The 'inside' model is considered to be at a quasi-steady-state condition because EBS has a relatively low thermal mass compared to the infinite geologic medium. The steady state calculation is performed at each time step with the heat source and interface temperature as boundary conditions. Future Work: Run Cyclus simulations with U.S. historical SNF inventory data, the spent fuel conditioning and repository models to study how waste package acceptance strategies impact repository loading.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Nonlinear Multiobjective MPC-Based Optimal Operation of a High Consistency Refining System in Papermaking

As one of the most important unit in the papermaking industry, the high consistency (HC) refining system is confronted with challenges such as improving pulp quality, energy saving, and emissions reduction in its operation processes. Here in this correspondence, an optimal operation of HC refining system is presented using nonlinear multiobjective model predictive control strategies that aim at set-point tracking objective of pulp quality, economic objective, and specific energy (SE) consumption objective, respectively. First, a set of input and output data at different times are employed to construct the subprocess model of the state process model for the HC refining system, and then the Wiener-type model can be obtained through combining the mechanism model of Canadian Standard Freeness and the state process model that determines their structures based on Akaike information criterion. Second, the multiobjective optimization strategy that optimizes both the set-point tracking objective of pulp quality and SE consumption is proposed simultaneously, which uses NSGA-II approach to obtain the Pareto optimal set. Furthermore, targeting at the set-point tracking objective of pulp quality, economic objective, and SE consumption objective, the sequential quadratic programming method is utilized to produce the optimal predictive controllers. In conclusion, the simulation results demonstrate that the proposed methods can make the HC refining system provide a better performance of set-point tracking of pulp quality when these predictive controllers are employed. In addition, while the optimal predictive controllers orienting with comprehensive economic objective and SE consumption objective, it has been shown that they have significantly reduced the energy consumption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Towards stacking fault energy engineering in FCC high entropy alloys

Stacking Fault Energy (SFE) is an intrinsic alloy property that governs much of the plastic deformation mechanisms observed in fcc alloys. While SFE has been recognized for many years as a key intrinsic mechanical property, its inference via experimental observations or prediction using, for example, computationally intensive first-principles methods is challenging. This difficulty precludes the explicit use of SFE as an alloy design parameter. In this work, we combine DFT calculations (with necessary configurational averaging), machine-learning (ML) and physics-based models to predict the SFE in the fcc CoCrFeMnNiV-Al high-entropy alloy space. The best-performing ML model is capable of accurately predicting the SFE of arbitrary compositions within this 7-element system. Finally, this efficient model along with a recently developed model to estimate intrinsic strength of fcc HEAs is used to explore the strength–SFE Pareto front, predicting new-candidate alloys with particularly interesting mechanical behavior.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Generalized Brunauer–Emmett–Teller Isotherm for Mixed-Gas Multilayer Adsorption Equilibria

Here, this work presents a rigorous thermodynamic framework to calculate mixed-gas multilayer adsorption equilibria from single-component isotherms and vapor–liquid equilibria. Named the generalized Brunauer–Emmett–Teller (gBET) isotherm, the newly formulated isotherm considers adsorbent surface heterogeneity, competitive adsorption on the monolayer, condensation–evaporation on the subsequent layers, and adsorbed phase nonideality for the monolayer and the subsequent layers. The monolayer adsorbed phase nonideality is tracked by using an area-based adsorption nonrandom two-liquid activity coefficient model. The adsorbed phase composition and corresponding nonideality in the subsequent layers are calculated at the dew point condition of the mixed gas with either an equation of state or an activity coefficient model for the vapor–liquid equilibria. The proposed model is validated with six single and three binary multilayer adsorption equilibrium systems, and the model results are compared against those from the classical BET isotherm for single-component adsorption and ideal adsorbed solution theory for mixed-gas adsorption equilibria.

09 BIOMASS FUELS↗

DOE OSTI2015

The millisecond magnetar central engine in short GRBs

One favored progenitor model for short duration gamma-ray bursts (GRBs) is the coalescence of two neutron stars (NS–NS). One possible outcome of such a merger would be a rapidly spinning, strongly magnetized neutron star (known as a millisecond magnetar). These magnetars may be “supra-massive,” implying that they would collapse to black holes after losing centrifugal support due to magnetic dipole spin down. By systematically analyzing the Burst Alert Telescope (BAT)-XRT light curves of all short GRBs detected by Swift, we test how consistent the data are with this central engine model of short GRBs. We find that the so-called “extended emission” feature observed with BAT in some short GRBs is fundamentally the same component as the “internal X-ray plateau” observed in many short GRBs, which is defined as a plateau in the light curve followed by a very rapid decay. Based on how likely a short GRB is to host a magnetar, we characterize the entire Swift short GRB sample into three categories: the “internal plateau” sample, the “external plateau” sample, and the “no plateau” sample. Based on the dipole spin-down model, we derive the physical parameters of the putative magnetars and check whether these parameters are consistent with expectations from the magnetar central engine model. The derived magnetar surface magnetic field B{sub p} and the initial spin period P{sub 0} fall into a reasonable range. No GRBs in the internal plateau sample have a total energy exceeding the maximum energy budget of a millisecond magnetar. Assuming that the beginning of the rapid fall phase at the end of the internal plateau is the collapse time of a supra-massive magnetar to a black hole, and applying the measured mass distribution of NS–NS systems in our Galaxy, we constrain the neutron star equation of state (EOS). The data suggest that the NS EOS is close to the GM1 model, which has a maximum non-rotating NS mass of M{sub TOV}∼2.37 M{sub ⊙}.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

FCC-ee: The Lepton Collider

Particle physics has arrived at an important moment of its history. The discovery of the Higgs boson, with a mass of 125 GeV, completes the matrix of particles and interactions that has constituted the “Standard Model” for several decades. This model is a consistent and predictive theory, which has so far proven successful at describing all phenomena accessible to collider experiments. On the other hand, several experimental facts do require the extension of the Standard Model and explanations are needed for observations such as the domination of matter over antimatter, the evidence for dark matter and the non-zero neutrino masses. Theoretical issues that need to be addressed include the hierarchy problem, the neutrality of the Universe, the stability of the Higgs boson mass upon quantum corrections and the strong CP problem. This report contains the description of a novel research infrastructure based on a highest-luminosity energy frontier electron-positron collider (FCC-ee) to address the open questions of modern physics. It will be a general precision instrument for the continued in-depth exploration of nature at the smallest scales, optimised to measure precisely the properties of the Higgs boson at the per-cent level, the Z and W bosons, the top quark and the Higgs coupling to the Z at the per-mil level. FCC-ee will provide unprecedented sensitivity to signs of new physics appearing either in the form of small deviations from the Standard Model or as rare decay processes. This collider will be implemented in stages, successively spanning the entire energy range from the Z pole over the WW threshold and H production peak to the t"t" ̅ threshold. Most of the infrastructure (e.g. underground structures, surface sites, electrical distribution, cooling & ventilation, RF systems) can be directly re-used for a subsequent highest-energy hadron collider (described in the FCC conceptual design report volume 3), serving the world-wide particle-physics community in a highly synergetic and cost-effective manner throughout the 21st century. The European Strategy for Particle Physics (ESPP) update 2013 stated “To stay at the forefront of particle physics, Europe needs to be in a position to propose an ambitious post-LHC accelerator project at CERN by the time of the next Strategy update”. The FCC study has implemented the ESPP recommendation by developing a long-term vision for an “accelerator project in a global context”. This document describes the detailed design and preparation of a construction project for a post-LHC circular lepton collider “in collaboration with national institutes, laboratories and universities worldwide”, and enhanced by a strong participation of industrial partners. Now, a coordinated preparation effort can be based on a core of an ever-growing consortium of already more than 135 institutes worldwide. The technology for constructing a high-energy, highest-luminosity circular lepton collider exists today. The FCC-ee concept comprises a power-saving twin-aperture magnet system, a continuous top-up injection scheme for stable operation and maximum integrated luminosity. Combined with an energy staging scheme, the FCC-ee represents the most efficient and most sustainable route for executing the research required to discover signs of new physics beyond the Standard Model. The step-wise energy increase of the FCC-ee does not require any additional civil engineering activities. Strategic R&D for FCC-ee aims at minimising construction cost and energy consumption, while maximising the socio-economic impact. It will mitigate residual technology-related risks and ensure that industry can benefit from an acceptable economic utility. Concerning the implementation, a preparatory phase of about eight years is both necessary and adequate to establish the project governance and organisation structures, building the international machine and experiment consortia, developing a territorial implementation plan in agreement with the host-states’ requirements, optimising the disposal of land and underground volumes and preparing the civil engineering project. Such a large-scale, international fundamental research infrastructure, tightly involving industrial partners and providing training at all education levels, will be a strong motor of economic and societal development in all participating nations. The FCC study has implemented a set of actions towards a coherent vision for the world-wide high-energy and particle physics community, providing a collaborative framework for topically complementary and geographically well-balanced contributions. This conceptual design report lays the foundation for a subsequent infrastructure preparatory and technical design phase.

43 PARTICLE ACCELERATORS↗

DOE OSTI2017

Water Quality Projects Summary for the Mid-Columbia and Cumberland River Systems

Scheduling and operational control of hydropower systems is accompanied with a keen awareness of the management of water use, environmental effects, and policy, especially within the context of strict water rights policy and generation maximization. This is a multi-objective problem for many hydropower systems, including the Cumberland and Mid-Columbia river systems. Though each of these two systems have distinct operational philosophies, hydrologic characteristics, and system dynamics, they both share a responsibility to effectively manage hydropower and the environment, which requires state-of-the art improvements in the approaches and applications for water quality modeling. The Department of Energy and Oak Ridge National Laboratory have developed tools for total dissolved gas (TDG) prediction on the Mid-Columbia River and a decision-support system used for hydropower generation and environmental optimization on the Cumberland River. In conjunction with IIHR - Hydroscience & Engineering, The University of Iowa and University of Colorado s Center for Advanced Decision Support for Water and Environmental Systems (CADSWES), ORNL has managed the development of a TDG predictive methodology at seven dams along the Mid-Columbia River and has enabled the ability to utilize this methodology for optimization of operations at these projects with the commercially available software package Riverware. ORNL has also managed the collaboration with Vanderbilt University and Lipscomb University to develop a state-of-the art method for reducing high-fidelity water quality modeling results into surrogate models which can be used effectively within the context of optimization efforts to maximize generation for a reservoir system based on environmental and policy constraints. The novel contribution of these efforts is the ability to predict water quality conditions with simplified methodologies at the same level of accuracy as more complex and resource intensive computing methods. These efforts were designed to incorporate well into existing hydropower and reservoir system scheduling models, with runtimes that are comparable to existing software tools. In addition, the transferability of these tools to assess other systems is enhanced due the use of simplistic and easily attainable values for inputs, straight-forward calibration of predictive equation coefficients, and standardized comparison of traditionally familiar outputs.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2011

Temperature-At-Depth Maps For the Conterminous US and Geothermal Resource Estimates

A third generation geothermal resource assessment has recently been completed for the conterminous US based on a revised heat flow map using over 35,000 data sites. Improvements include: nearly doubling the number of data points used in the analysis, more detailed thermal conductivity models for temperature-at-depth and heat flow calculations, and addition of a significant number of calibration wells as checks on the bottom hole temperature (BHT) correction. The results increase the accuracy of temperature-at-depth models for the conterminous US. These temperature models are the key input required for evaluating the non-conventional geothermal resources on a regional to sub-regional basis. The new resource assessment was prepared according to a proposed global protocol for estimating Enhanced/ Engineered Geothermal Systems (EGS) resource potential. A comparison of the new assessment approach with previous studies is provided, along with a discussion of the differences associated with the revised approach.

15 GEOTHERMAL ENERGY↗

DOE OSTI2020

An Update to the NREL Baseline Wind Turbine Controller: Preprint

The NREL 5MW wind turbine model is well established as an industry standard and is often used as a comparison model, or a model on which to build upon. Though effective, the legacy controller for the NREL 5MW wind turbine is built on a simple algorithm that is not up to date with many industry standards. Additionally, as the research community has advanced into more fast-paced development cycles, as systems engineering tools such as WISDEM \cite{WISDEM} are employed, and as a greater focus on controls co-design practices is encouraged, a demand for a generic wind turbine controller has arisen. This work presents updates for the NREL 5MW baseline controller to a more modern control architecture, and establishes a generic tuning framework that can be easily adapted to various wind turbines. Based on initial results, the updated generic controller eases the automatic tuning process, while maintaining or improving upon the performance of the legacy NREL 5MW controller.

17 WIND ENERGY↗

DOE OSTI2021

Cybersecurity concerns for the energy sector in the maritime domain

The world has seen a number of high-profile maritime disasters in recent months and years, and has felt the impact of them. At the same time, the world has also seen a number of high-profile cyberattacks. It has felt their impact, as well. And, likely no sector has been more affected by the maritime and cyber incidents than the energy sector, as fuel prices often spike or trough, and access to energy resources can become an instant source of concern, tension, or even conflict. As energy sectors—in all their forms—continue to rely on the maritime domain or even increase that reliance, they must be mindful that traditional maritime threats—like piracy, theft, and weather events—are not the only threats they face today. Maritime cybersecurity concerns are among the most potentially disruptive to energy-sector interests and, yet, are among the least understood and least addressed. This paper identifies nine areas in which the energy sector faces harmful cyber vulnerabilities in the maritime domain, to provide enough insight and examples to allow for action to be taken to reduce the risk of harm from these different vulnerabilities. The paper develops the example of offshore wind energy to model how to assess cyber considerations more fully. Ultimately, it concludes with a series of recommendations that offer policymakers, energy-sector actors, and security and law-enforcement professionals steps to minimize the exposure of the maritime energy sector to harmful cyberattacks.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2014

An efficient optimization of well placement and control for a geothermal prospect under geological uncertainty

This work applies an efficient optimization technique based on a multivariate adaptive regression spline (MARS) technique to determine the optimal design and engineering of a potential geothermal production operation at a prospect near Superstition Mountain in Southern California, USA. The faster MARS-based statistical model is used as a surrogate for higher-fidelity physical models within the intensive optimization process. Its use allows for the exploration of the impacts of specific engineering design parameters in the context of geologic uncertainty as a means to both understand and maximize profitability of the production operation. The MARS model is initially developed from a training dataset generated by a finite set of computationally complex hydrothermal models applied to the prospect. Its application reveals that the optimal engineering design variables can differ considerably assuming different choices of hydrothermal flow properties, which, in turn, indicates the importance of reducing the uncertainty of key geologic properties. The major uncertainty sources in the natural-system are identified and ranked first by an efficient MARS-enabled total order sensitivity quantification, which is then used to assist evaluating the effect of geological uncertainties on optimized results. At the Southern California prospect, this parameter sensitivity analysis suggests that groundwater circulation through high permeable structures, rather than heat conduction through impermeable granite, is the primary heat transfer method during geothermal extraction. Reservoir histories simulated using optimal parameters with different constraints are analyzed and compared to investigate the longevity and maximum profit of the geothermal resources. The comparison shows that the longevity and profit are very likely to be overestimated by optimizations without appropriate constraints on natural conditions. In addition to geothermal energy production, this optimization approach can also be used to manage other geologic resource operations, such as hydrocarbon production or CO 2 sequestration, under uncertain reservoir conditions.

15 GEOTHERMAL ENERGY↗

DOE OSTI2014

Development of SFR Primary System Simulation Capability for Advanced System Codes

Under the Reactor Product Line (RPL) of DOE/NE’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, an SFR System Analysis Module is being developed at Argonne National Laboratory for whole-plant safety analysis. This tool will simulate tightly coupled physical phenomena – including nuclear fission, heat transfer, fluid dynamics, and thermal-mechanical response – in SFR structures, systems, and components. It is based on the MOOSE (Multi-physics Object-Oriented Simulation Environment) framework, which relies upon open-source libraries such as libMesh and PETSc for mesh generation, finite element analysis, and numerical solutions. This development is a coordinated effort along with the development of RELAP-7, which is an advanced safety analysis tool for light-water reactors developed at Idaho National Laboratory. The SFR Module is aimed to model and simulate the SFR systems with much higher fidelity and with well-defined and validated prediction capabilities. It will provide fast-running, modest-fidelity, whole-plant transient analyses capability, which is essential for fast turnaround design scoping and engineering analyses.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2020

Computational model for predicting the performance of fluid-powered longiudinal piston modules and motors.

A Matlab-based computational model line code has been developed for predicting the performance of fluid-powered longitudinal piston modules and motors. A system of equations has been developed based upon applying the conservation of mass to a control volume defined by a reciprocating piston. The method results in a differential equation that predicts the pressure gradient in the control volume as a function of rotor rotation angle. The model uses an integration scheme to predict the pressure state in the control volume. The orifice equation is used to predict the flowrate in and out of the control volume. From the resulting solution the torque and speed characteristics of the motor configuration can be predicted, optimized, or tailored for a specific requirement.SAND2019-13983 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Taylor, Michael↗

DOE OSTI2019

Gas-Induced Motion of a Piston in a Vibrated Liquid-Filled Housing

We present that models and experiments are developed to investigate how a small amount of gas can cause large rectified motion of a piston in a vibrated liquid-filled housing when piston drag depends on piston position so that damping is nonlinear even for viscous flow. Two bellows serve as surrogates for the upper and lower gas regions maintained by Bjerknes forces. Without the bellows, piston motion is highly damped. With the bellows, the piston, the liquid, and the two bellows move together so that almost no liquid is forced through the gaps between the piston and the housing. This Couette mode has low damping and a strong resonance: the piston and the liquid vibrate against the spring formed by the two bellows (like the pneumatic spring formed by the gas regions). Near this resonance, the piston motion becomes large, and the nonlinear damping produces a large rectified force that pushes the piston downward against its spring suspension. A recently developed model based on quasi-steady Stokes flow is applied to this system. A drift model is developed from the full model and used to determine the equilibrium piston position as a function of vibration amplitude and frequency. Corresponding experiments are performed for two different systems. In the two-spring system, the piston is suspended against gravity between upper and lower springs. Lastly, in the spring-stop system, the piston is pushed up against a stop by a lower spring. Model and experimental results agree closely for both systems and for different bellows properties.

42 ENGINEERING↗

DOE OSTI2021

Dynamic Process Intensification via Data-Driven Dynamic Optimization: Concept and Application to Ternary Distillation

Process intensification is a design philosophy aimed at making chemical processes safer and more efficient. Its implementation often results in significant modifications to the design and structure of the process, with several conventional unit operations occurring in the same physical device. Traditionally, process intensification has focused on steady-state operation. In our previous works, we introduced dynamic process intensification (DPI) as a new intensification paradigm based on operational changes for conventional or intensified units. DPI is predicated on switching operation between two auxiliary steady states selected via a steady-state optimization calculation that ensures that the system generates, on average and over time, the same products as in nominal steady-state operation, but with favorable economics. This paper extends the DPI concept and introduces a novel dynamic optimization-based DPI strategy (Do-DPI) that involves imposing a true cyclic operation rather than switching between two discrete states. We discuss its implementation using surrogate dynamic models learned via system identification. Here, an extensive case study concerning a ternary distillation column separating a canonical hydrocarbon mixture shows that Do-DPI can reduce energy use by more than 4% relative to steady-state operation, with no significant deviations in product quality and production rate.

42 ENGINEERING↗

DOE OSTI2020

Correlating dynamic microstructure to observed color in electrophoretic displays via in situ small-angle x-ray scattering

Electrophoretic deposition (EPD) is an industrially relevant and scalable technique used to form particle deposits from colloidal suspensions. Highly concentrated particle suspensions generally prevent real-time in situ microscopy observations which limit the characterization of EPD films to ex situ, or postprocessed, laboratory techniques. For dynamic systems, such as tunable amorphous photonic crystals (APCs), only reversible deposits are formed during the EPD process. Since reversible deposits cannot be characterized with standard ex situ methods, the particle-particle and particle-field interactions that govern the displayed color and crystallinity of these systems are not well understood. In this paper, we present in situ small-angle x-ray scattering and UV-Vis techniques for measuring both the structural and optical response of an APC under applied electric fields. Furthermore, we also develop a computational model based on colloidal interactions to explain the observed change in the interparticle spacing of APCs due to the applied electric field which correlates to displayed color. Ultimately, this work provides a new in situ characterization method that could be expanded for other dynamic, tunable colloidal systems.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Environmental Protection Coating System for Refractory Metal Alloys (EPCS for RMAs)

As part of ARPA-E’s Ultra High Temperature Impervious Materials Advancing Turbine Efficiency (UITIMATE) program, this project aims to develop an environmental protection coating system (EPCS) for refractory metal alloys (RMAs) – which will provide radical improvement in long term protection for ultra-high temperature refractory metal components in harsh gas-turbine environments. The drive for higher fuel efficiency and higher core power of gas turbines used in electric power generation and in aircraft propulsion requires higher peak operation temperatures. The temperature capability of state-of-the-art materials cannot meet the new requirements. Refractory metal alloys have desirable capabilities for achieving the required peak temperatures, but most of them are subject to oxidation in the gas turbine environment. Thus, there is a strong need to develop novel environmental protective coatings that enable the refractory metals to operate in an ultra-high temperature engine environment. This project is composed of four major technical innovations that can provide a potentially transformational solution in providing environmental protection for refractory metal alloys over a wide range of temperature. 1) Multi-layer self-healing environmental barrier coating (EBC) that provides protection against combustion gas environment. 2) Oxidation resistant diffusion barrier (DB) on the alloy surface to enhance coating stability. 3) Synergistic integration of the multi-layer self-healing EBC with the diffusion barrier to extend coating life. 4) Guidance of physics-based modeling to accelerate coating development and optimization. Our team has successfully developed a multi-layer self-healing environmental protection coating system (EPCS) that can provide oxidation protection for commercially available molybdenum based refractory metal alloys over a wide temperature range of up to 1600 °C for fuel-efficient gas turbine applications. The team also developed a multi-layer high temperature coating design tool to accelerate coating development and optimization based on physics-based modeling. The team also engaged RTX business unite, notable Pratt and Whitney, for future commercialization of this technology. The successful completion of this Phase I effort led to the selection of performing Phase II of the program. In Phase II, the team plans to apply the EPCS in the protection of a newly discovered molybdenum-based metal alloy which has the potential of superior high temperature properties to the commercial products. Th coating will be evaluated under test conditions and environment that mimic gas turbine operation.

36 MATERIALS SCIENCE↗