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All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Aerocapture: An Enabling Technology for Flagship-Class Uranus Orbiter and Probe Mission

Introduction: The current decadal survey published by the National Academies of Sciences has informed National Aeronautics and Space Administration (NASA) to prioritize the study of the Ice Giants, especially Uranus. To gather the required data that addresses the science questions raised in this survey, a mission to Uranus with an orbiter and atmospheric probe must be designed. The Uranus Orbiter and Probe (UOP) study, which the survey identified as the flagship mission of this decade, proposes a 2031 launch to take advantage of a Jupiter fly-by and utilizes a fully propulsive orbit insertion design with an Earth-to-Uranus transit times ranging from 13 to 15 years. This fully propulsive orbit insertion at Uranus will be very fuel expensive (wet mass percentages of around 60-70\%) thereby leaving less mass for the scientific payload and additional planetary probes. In addition, scientists are more interested in visiting Uranus before 2049, when the Spring Equinox will occur, as it allows studying Uranus seasons not seen during Voyager 2's flyby in 1987. A NASA Flagship-Class mission would require at least 10 years of lead time prior to launch thereby making the 2031 launch to take advantage of the Jupiter fly-by extremely challenging. The consequence of missing the Jupiter fly-by and launching in the late 2030s is the challenge of a fully-propulsive mission like UOP to have a feasible alternative interplanetary trajectory that reaches Uranus before 2050. As an alternative, to address the shortcomings of the fully propulsive mission, one can design a mission to Uranus using aerocapture. What is aerocapture: Aerocapture is an atmospheric maneuver that uses aerodynamic forces generated by flight within a planetary atmosphere to decelerate and achieve orbit insertion. Using aerocapture allows one to provide the change in velocity (Delta V) needed to slow down from the approach hyperbolic trajectory to achieve the desired captured orbit around the target planet using aerodynamic forces of the vehicle (lift and drag). Using aerodynamic forces instead of fully-propulsive maneuvers results in significant savings in the fuel. Furthermore, aerocapture can also allow one to consider interplanetary trajectories with higher approach hyperbolic velocities, thus reducing the mission transit times. Aerocapture as an enabling technology: To use aerocapture as an enabling technology for the Uranus exploration mission, one would require an integrated system-level design, including a Thermal Protection System (TPS), hardware needed for aerodynamic modulation, and autonomous Guidance, Navigation, and Control (GNC) systems. Aerocapture has yet to be demonstrated, despite considering it for several past missions. Recent advancements in TPS and GNC capabilities show the potential for using rigid, heritage entry vehicle configurations already flown at other planetary bodies for Uranus aerocapture. Aerocapture can be a robust technology that can deliver spacecraft to Uranus science orbits while substantially increasing on-orbit payload mass (more than 40\%) that can enable robust atmospheric entry probes. Additionally, the aerocapture maneuver would reduce the interplanetary transit time by 2–5 years (15-30\%) relative to fully-propulsive orbit insertion. Recent work has shown that one can conduct a flagship-class mission in a shorter period than fully-propulsive missions if using aerocapture. What does aerocapture bring in for a Uranus Mission: Using aerocapture for a Uranus orbiter and atmospheric probe mission can provide one with considerable propellant savings. Spacecraft in interplanetary trajectories to Uranus typically need an Delta V in orders of kilometers per second to insert into science orbit. One would require thousands of kilograms of fuel to achieve such a Delta V using a traditional fully propulsive maneuver, leaving less mass for payload during the mission launch. Aerocapture can reduce the propulsion needs by dissipating energy in the sizable atmosphere of Uranus without a significant mass increase due to the need for an aeroshell. One can use the mass savings achieved using the aerocapture to reduce the launch vehicle requirements. In addition, one can also have additional science instruments on the orbiter or create a robust instrumentation suite on an atmospheric probe that can significantly increase the science outcome of the Uranus exploration mission. Furthermore, since aerocapture performance is relatively insensitive to increases in hyperbolic excess velocity, one can design the interplanetary trajectory to arrive at Uranus faster, reducing the interplanetary transit time and operations cost. All these savings, achieved using aerocapture, could help fit a larger class mission, such as the Uranus mission within a smaller capital, e.g., a Flagship-class orbiter mission in a New Frontiers class capital. Summary: This talk will provide an overview of how aerocapture can enable the Uranus exploration mission. Specifically, this talk will discuss the latest advancements made in the Uranus aerocapture study, such as investigating interplanetary trajectories with higher hyperbolic approach velocities and their implications on the aero heating and the TPS design, incorporating FNPAG (an advanced numerical-predictor guidance) and comparison of multiple navigation approaches. In addition, this talk will focus on mechanical design that can house more than one atmospheric probe and the six degrees of freedom simulation of aerocapture at Uranus. Findings from a recent NASA Space Technology Mission Directorate (STMD)-funded activity studying the aerocapture as an enabling technology for a Uranus orbiter will be presented. Using the science payload recommended by the Decadal Survey for Uranus exploration, this work shows many improvements over the baseline fully-propulsive mission. These improvements include a shorter cruise phase, flexibility in launch opportunities late into the 2030s while reaching Uranus before the 2050 equinox for the desired science opportunities, and lower propellant mass needs. This talk will highlight how aerocapture can be utilized for Uranus science orbit insertion using a lower-risk, heritage entry vehicle configuration used extensively as a Mars entry, descent, and landing vehicle. Furthermore, this talk will explore how the demonstration of aerocapture at Earth can benefit the aerocapture-enabled Uranus mission.

Aerocapture↗
DOE OSTI2024

Integrated protonic ceramic electrochemical cell for sustainable energy economy using water-energy nexus framework

Reliance on fossil fuels will continue for the next decades even though there are global pushes away from it to mitigate the overarching climate challenge, most especially by its highest consumers and availability. While there is a hastening global shift away from fossil fuel, integrating its assets into this technology helps limit the risk and future losses of stranded assets and reduce the cost of investment in the new technologies. Moreover, the generation of electricity from intermittent renewable sources like solar and wind has witnessed a significant surge in recent years, leading to a pressing demand for practical energy storage systems. Electrical energy storage is anticipated to play a pivotal role in the future global energy system, facilitating load-leveling operations to support the greater integration of renewable and distributed generation. Reversible electrochemical cells (RECs) offer a promising option for addressing the fossil fuel assets integration and energy storage challenges through the interconversion between electrical and chemical energy and concurrent utilizing carbon emission. In their electrolysis mode, the RECs convert electricity into durable, storable, and portable valuable chemical fuels such as syngas and methane. Conversely, the produced chemical fuels can be used as reactants in the fuel cell mode to generate electricity on demand with minimal (hydrocarbons) or zero when H2 or NH3 is used emissions. However, a challenging goal for this type of technology remains to achieve optimal operation and high roundtrip efficiencies, which has hindered the deployment of previous electrochemical cells. This dissertation demonstrates how reversible protonic ceramic electrochemical cells (RePCECs) can be integrated with fossil fuel power plants and renewable energy sources as a potential energy storage system. In this work, integrated RePCEC systems are designed and examined using computational modeling at scales to determine appropriate system configurations and operating conditions that achieve high roundtrip efficiencies. Cell level design of the PCEC is the first approach, several cells are assembled for the stack level model that is integrated into combined cycle powerplant and solar photovoltaic for the system level model. After critical literature review, this answered the operational and integration research questions proposed to address these challenges. The designed systems perform two functions, utilizing captured CO2 and storing renewable energy through co-electrolysis of steam and CO2. The co-electrolysis reaction involves endothermic water electrolysis and exothermic methanation reaction. To enhance high roundtrip efficiency, there is a need for thermal balance and management in the electrolysis mode. This involves operating the RePCEC stack under conditions that favor methane production to balance out heat needed by water electrolysis, it crucial for the RePCEC system operation. Methanation is enhanced by low temperatures. Leveraging on fabricated BCZYYb-electrolyte RePCEC, the cell model designed revealed that the optimum temperature for methane production is 450℃ at atmospheric pressure. Thus, to achieve optimum system performance, operating in the temperature range 450-525℃ is recommended at the given configuration, combining between the optimum temperature for methane production and temperature for the optimum stack roundtrip efficiency. Configuration with carbon capture system and purge stream is the optimum configuration from the seven conceptualized and evaluated. The modeling outcomes include a thermodynamic examination of integrated RePCEC systems, calibration of cell and stack level models, and steady-state simulation and integration into a 600MW combined cycle power plant retrofitted with two two-stage membrane-based carbon capture system and a wastewater treatment and recovery unit. At 100% powerplant loading, the stack and system roundtrip efficiencies are 72% and 51.37% respectively. Adding a purge stream for produced hydrogen at the system downstream improves the efficiencies to 74 and 55.48% respectively. At atmospheric pressure and 525℃, the system model suggests that a stack roundtrip of 82% is achievable, and overall system efficiency increases by reducing the energy consumption by the balance of plant components for steam generation and storage. Economic analysis of the process gives levelized cost of methane as $2.24/MMBtu lower than the conventional production route that range between $3.46/MMBtu and $9.85/MMBtu. The lifecycle analysis shows that the global warming potential for the production of methane and hydrogen from the RePCEC system is 3.83 kg CO2 eq which is lower than 9.35 kg CO2 eq emission during steam methane reforming for hydrogen production. This answered both the environmental and economic concerns in the raised research question. The proposed RePCEC configuration and analysis carried out in this dissertation to address the surge in renewable energy and challenges with PCEC technology hold significant potential in achieving large-scale energy storage while simultaneously reducing carbon emissions. These advancements, coupled with suitable governmental policies and incentive programs, have the potential to economically disrupt the natural gas industries by using RePCEC systems for methane production, thereby making them more favorable for eventual implementation and commercialization.

25 ENERGY STORAGE↗
DOE OSTI2021

Textured Electrodes: Manipulating Built-In Crystallographic Heterogeneity of Metal Electrodes via Severe Plastic Deformation

Control of crystallography of metal electrodeposit films has recently emerged as a key to achieving long operating lifetimes in next-generation batteries. It is reported that the large crystallographic heterogeneity, e.g., broad orientational distribution, that appears characteristic of commercial metal foils, results in rough morphology upon plating/stripping. On this basis, an accumulative roll bonding (ARB) methodology—a severe plastic deformation process—is developed. Zn metal is used as a first example to interrogate the concept. It is demonstrated that the ARB process is highly effective in achieving uniform crystallographic control on macroscopic materials. After the ARB process, the Zn grains exhibit a strong (002) texture (i.e., [002] Zn //ND). The texture transitions from a classical bipolar pattern to a nonclassical unipolar pattern under large nominal strain eliminate the orientational heterogeneity of the foil. The strongly (002)-textured Zn remarkably improves the plating/stripping performance by nearly two orders of magnitude under practical conditions. The performance improvements are readily scaled to achieve pouch-type full batteries that deliver exceptional reversibility. The ARB process can, in principle, be applied to any metal chemistry to achieve similar crystallographic uniformity, provided the appropriate temperature and accumulated strains are employed. Here this concept is evaluated using commercial Li and Na foils, which, unlike Zn (HCP), are BCC crystals. The simple process for creating strong textures in both hexagonal and cubic metals and illustrating the critical role such built-in crystallography plays underscores opportunities for developing highly reversible thin metal anodes (e.g., hexagonal Zn, Mg, and cubic Li, Na, Ca, Al).

36 MATERIALS SCIENCE↗
DOE OSTI2024

Giant Apparent Optical Circular Dichroism in Thin Films of Bismuth-Based Hybrid Organic-Inorganic Metal Halide Semiconductor Through Preferred Orientation

Introducing chirality into organic/inorganic hybrid materials can impart chiroptical properties such as circular dichroism. The ability to tune chiroptical properties in self-assembled materials can have important implications for spintronic and optoelectronic applications. Here, a chiral organic cation, (R/S)-4-methoxy-a-methylbenzylammonium, is incorporated to synthesize the bismuth-based hybrid organic-inorganic metal halide semiconductor, (R/S-MeOMePMA)BiI4. Thin films of this Bi-based compound demonstrate large chiroptical responses, with circular dichroism anisotropy (gCD) values up to ˜0.1, close to the highest value observed in another chiral metal-halide semiconductor, (R-MBA2CuCl4). Detailed investigation reveals that this large gCD in (R/S-MeOMePMA)BiI4 is caused by the apparent CD effect. Careful selection of deposition conditions and the concomitant thin-film orientation enables the control of gCD, with maximum value observed when its thin film has a well-crystallized preferred (001) orientation parallel to the substrate. The results support a growing body of evidence that low symmetry plays an important role in achieving unusually large gCD in these chiral metal-halide materials and provides design rules for achieving large chiroptical response via morphology control.

chiroptic response↗
DOE OSTI2020

A Fluorination Method for Improving Cation-Disordered Rocksalt Cathode Performance

In Li-rich cation-disordered rocksalt oxide cathodes (DRX), partial fluorine substitution in the oxygen anion sublattice can increase the capacity contribution from transition-metal (TM) redox while reducing that from the less reversible oxygen redox. To date, limited fluorination substitution has been achieved by introducing LiF precursor during the solid-state synthesis. To take full advantage of the fluorination effect, however, a higher F content is desired. In the present study, the successful use of a fluorinated polymeric precursor is reported to increase the F solubility in DRX and the incorporation of F content up to 10–12.5 at% into the rocksalt lattice of a model Li-Mn-Nb-O (LMNO) system, largely exceeding the 7.5 at% limit achieved with LiF synthesis. Higher F content in the fluorinated-DRX (F-DRX) significantly improves electrochemical performance, with a reversible discharge capacity of ≈255 mAh g –1 achieved at 10 at% of F substitution. After 30 cycles, up to a 40% increase in capacity retention is achieved through the fluorination. Overall, the study demonstrates the feasibility of using a new and effective fluorination process to synthesize advanced DRX cathode materials.

25 ENERGY STORAGE↗
DOE OSTI2023

High Sulfur Loading and Capacity Retention in Bilayer Garnet Sulfurized‐Polyacrylonitrile/Lithium‐Metal Batteries with Gel Polymer Electrolytes

The cubic‐garnet (Li 7 La 3 Zr 2 O 12 , LLZO) lithium–sulfur battery shows great promise in the pursuit of achieving high energy densities. The sulfur used in the cathodes is abundant, inexpensive, and possesses high specific capacity. In addition, LLZO displays excellent chemical stability with Li metal; however, the instabilities in the sulfur cathode/LLZO interface can lead to performance degradation that limits the development of these batteries. Therefore, it is critical to resolve these interfacial challenges to achieve stable cycling. Here, an innovative gel polymer buffer layer to stabilize the sulfur cathode/LLZO interface is created. Employing a thin bilayer LLZO (dense/porous) architecture as a solid electrolyte and significantly high sulfur loading of 5.2 mg cm −2 , stable cycling is achieved with a high initial discharge capacity of 1542 mAh g −1 (discharge current density of 0.87 mA cm −2 ) and an average discharge capacity of 1218 mAh g −1 (discharge current density of 1.74 mA cm −2 ) with 80% capacity retention over 265 cycles, at room temperature (22 °C) and without applied pressure. Achieving such stability with high sulfur loading is a major step in the development of potentially commercial garnet lithium–sulfur batteries.

25 ENERGY STORAGE↗
DOE OSTI2020

Shape-constrained Input Estimation for Efficient Multi-shaker Vibration Testing

Multi-shaker vibration testing is gaining interest from structural dynamics test engineers as it can provide a much more accurate match to complicated field vibration responses than traditional single-axis shaker tests. However, the force capabilities of the small modal shakers typically used in multi-shaker vibration tests has limited the achievable response levels. To date, most multi-shaker vibration tests have been performed using a variety of standard, commercially-available control systems. While these control systems are adequate for a wide range of multiple-input/multiple-output tests, their control algorithms have not been tailored for the specific problem of multi-shaker vibration tests: efficiently coordinating the various shakers to work together to achieve a desired response. Here, a new input estimation algorithm is developed and demonstrated using simulations and actual test data. This algorithm, dubbed shape-constrained input estimation, is shown to effectively coordinate multiple shakers using a set of constraint vectors based on the deflection shapes of the test structure. This is accomplished by using the singular vector shapes of the system frequency response matrix, which allows the constraint vectors to automatically change as a function of frequency. Simulation and test results indicate a significant reduction in the input forces required to achieve a desired response. Finally, the results indicate that shape-constrained input estimation is an effective method to achieve higher response levels from limited shaker forces which will enable higher level multi-shaker vibration tests to be performed.

42 ENGINEERING↗
DOE OSTI2020

Reinforcement learning based automated history matching for improved hydrocarbon production forecast

History matching aims to find a numerical reservoir model that can be used to predict the reservoir performance. An engineer and model calibration (data inversion) method are required to adjust various parameters/properties of the numerical model in order to match the reservoir production history. In this study, we develop deep neural networks within the reinforcement learning framework to achieve automated history matching that will reduce engineers’ efforts, human bias, automatically and intelligently explore the parameter space, and remove the need of large set of labeled training data. To that end, a fast-marching-based reservoir simulator is encapsulated as an environment for the proposed reinforcement learning. The deep neural-network-based learning agent interacts with the reservoir simulator within reinforcement learning framework to achieve the automated history matching. Reinforcement learning techniques, such as discrete Deep Q Network and continuous Deep Deterministic Policy Gradients, are used toth, used to train the learning agents. The continuous actions enable the Deep Deterministic Policy Gradients to explore more states at each iteration in a a learning episode; consequently, a better history matching is achieved using this algorithm as compared to Deep Q Network. For simplified dual-target composite reservoir models, the best history-matching performances of the discrete and continuous learning methods in terms of normalized root mean square errors are 0.0447 and 0.0038, respectively. Furthermore, our study shows that continuous action space achieved by the deep deterministic policy gradient drastically outperforms deep Q network.

42 ENGINEERING↗
DOE OSTI2024

Scientists’ call to action: Microbes, planetary health, and the Sustainable Development Goals

Microorganisms, including bacteria, archaea, viruses, fungi, and protists, are essential to life on Earth and the functioning of the biosphere. Here, we discuss the key roles of microorganisms in achieving the United Nations Sustainable Development Goals (SDGs), highlighting recent and emerging advances in microbial research and technology that can facilitate our transition toward a sustainable future. Given the central role of microorganisms in the biochemical processing of elements, synthesizing new materials, supporting human health, and facilitating life in managed and natural landscapes, microbial research and technologies are directly or indirectly relevant for achieving each of the SDGs. More importantly, the ubiquitous and global role of microbes means that they present new opportunities for synergistically accelerating progress toward multiple sustainability goals. By effectively managing microbial health, we can achieve solutions that address multiple sustainability targets ranging from climate and human health to food and energy production. Emerging international policy frameworks should reflect the vital importance of microorganisms in achieving a sustainable future.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Recent developments in catalyst-related PEM fuel cell durability

Cost and durability remain the two major barriers to the widespread commercialization of polymer electrolyte membrane fuel cell (PEMFC)-based power systems, especially for the most impactful but challenging fuel cell electric vehicle (FCEV) application. Commercial FCEVs are now on the road; however, their PEMFC systems do not meet the cost targets established by the U.S. Department of Energy, primarily due to the high platinum loading needed on the cathode to achieve the requisite performance and lifetime. Furthermore, while the activities of a number of commercial Pt-based alloy cathode catalysts exceed the beginning-of-life (BOL) targets, these activities, and the overall cathode performance, degrade via a variety of mechanisms described herein. Degradation is mitigated in current FCEVs by utilizing a cathode catalyst with a lower BOL activity (e.g., much lower transition metal alloy content and larger BOL nanoparticle size), necessitating higher catalyst loadings, and through the utilization of system controls that avoid conditions known to exacerbate degradation processes, such as limiting the fuel cell stack voltage range. The design and development of active and robust materials and eliminating the need for vehicle mitigation strategies would greatly simplify the operating system, allowing for greater transient operation, avoiding large hybridization, and curtailing of fuel cell power. Although system mitigation strategies have provided the near-term pathway for FCEV commercialization, material-specific solutions are required to further reduce costs and improve operability and efficiency. Future material developments should focus on stabilization of the electrode structure and minimization of the catalyst particle susceptibility to dissolution caused by oxide formation and reduction over PEMFC cathode-relevant operating potentials plus minimization of support corrosion. Ex situ accelerated stress tests have provided insight into the processes responsible for material and performance degradation and will continue to provide useful information on the relative stability of materials and benchmarks for robust and stable materials-based solutions not requiring system mitigation strategies to achieve adequate lifetime.

25 ENERGY STORAGE↗
DOE OSTI2021

Finite-rate entrainment effects on nitrogen oxide (NO x ) emissions in staged combustors

Axially staged combustors offer the potential for achieving low NO x emissions from gas turbines at the elevated temperatures required to achieve at least 65% combined cycle efficiencies. While there is evidence that premixing between the main burner products and secondary stream reduces NO x , it is important to characterize the specific requirements needed to achieve low emissions at gas turbine conditions. This study examines the sensitivity of NO x to finite-rate, large-scale entrainment of the main and secondary streams under the simplifying assumption of infinitely-fast small-scale mixing. Essentially, this allows us to isolate the effects of limited large-scale entrainment rates by using a homogeneous/uniform condition for the entrained and reacting gases. We use a reduced-order reactor network model to examine a generic staged-combustor whose inputs are physical time scales that embody the finite-rate entrainment characteristics. With simulations conducted over a large parameter space at typical operating conditions (25 atm, 650 K air), the results show that, even when small-scale mixing is infinitely fast and the reaction zone is uniform, entrainment significantly affects NO x emissions due to its influence on the equivalence ratio — and thus the temperature and time — at which the entrained mixture ignites. Fuel-air staging is shown to be vital to NO x reduction in most practical cases where entrainment times exceed roughly 1 ms and the secondary stream finishes entraining before the main burner products. A constrained NO x minimization indicates that using the leanest possible main burner and re-routing as much air as possible to the secondary stage is key to low NO x with finite-rate entrainment; for example, less than 10 ppm NO x can be achieved if the secondary stage contains 20% of the total mass flow.

03 NATURAL GAS↗
DOE OSTI2025

De-Risking High-Recovery Brackish Water Desalination via Flow Reversal and Feed Flushing Using Techno-Economic Assessment

Novel desalination technologies have demonstrated enhanced performance and improved financial metrics over existing processes adopted by industry. Establishing quantitative performance targets is essential for achieving financial benefits over the current state of the art. Herein, we demonstrate how WaterTAP, a techno-economic assessment (TEA) tool, can be used to identify minimum performance metrics necessary to achieve financial benefit over using existing processes. This study evaluates the feasibility of increasing water recovery at the Chino Desalter I above 90 % through the addition of a third variable configuration reverse osmosis (VCRO) stage. Sensitivity analyses revealed flow reversal frequency, feed flushing volume (used as a cleaning step), and membrane lifespan are key factors influencing the financial viability of the VCRO process. The TEA analysis demonstrated that the system must achieve a recovery of 84 % and a 1-year membrane lifespan to have a breakeven LCOW, while achieving 90 % recovery can ultimately reduce the LCOW by 16 %. Notably, a trade-off between decreasing frictional losses and increased osmotic pressure across the recovery range, resulted in a stable specific energy consumption across the recovery range, enabling meaningful LCOW reductions without an energy penalty, a key finding that contrasts with conventional RO. This work demonstrates how TEA can guide system design by identifying key performance targets and exploring trade-offs, enabling data-driven decisions to de-risk innovative processes. These findings underscore the importance of leveraging TEA to evaluate scaling mitigation strategies and optimize inland desalination systems for sustainable and cost-effective operation.

14 SOLAR ENERGY↗
DOE OSTI2023

Deep learning uncertainty quantification for clinical text classification

Machine learning algorithms are expected to work side-by-side with humans in decision-making pipelines. Thus, the ability of classifiers to make reliable decisions is of paramount importance. Deep neural networks (DNNs) represent the state-of-the-art models to address real-world classification. Although the strength of activation in DNNs is often correlated with the network’s confidence, in-depth analyses are needed to establish whether they are well calibrated. In this paper, we demonstrate the use of DNN-based classification tools to benefit cancer registries by automating information extraction of disease at diagnosis and at surgery from electronic text pathology reports from the US National Cancer Institute (NCI) Surveillance, Epidemiology, and End Results (SEER) population-based cancer registries. In particular, we introduce multiple methods for selective classification to achieve a target level of accuracy on multiple classification tasks while minimizing the rejection amount—that is, the number of electronic pathology reports for which the model’s predictions are unreliable. We evaluate the proposed methods by comparing our approach with the current in-house deep learning-based abstaining classifier. Overall, all the proposed selective classification methods effectively allow for achieving the targeted level of accuracy or higher in a trade-off analysis aimed to minimize the rejection rate. On in-distribution validation and holdout test data, with all the proposed methods, we achieve on all tasks the required target level of accuracy with a lower rejection rate than the deep abstaining classifier (DAC). Interpreting the results for the out-of-distribution test data is more complex; nevertheless, in this case as well, the rejection rate from the best among the proposed methods achieving 97% accuracy or higher is lower than the rejection rate based on the DAC. We show that although both approaches can flag those samples that should be manually reviewed and labeled by human annotators, the newly proposed methods retain a larger fraction and do so without retraining—thus offering a reduced computational cost compared with the in-house deep learning-based abstaining classifier.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

A generalized approximate control variate framework for multifidelity uncertainty quantification

We describe and analyze a variance reduction approach for Monte Carlo (MC) sampling that accelerates the estimation of statistics of computationally expensive simulation models using an ensemble of models with lower cost. These lower cost models — which are typically lower fidelity with unknown statistics — are used to reduce the variance in statistical estimators relative to a MC estimator with equivalent cost. We derive the conditions under which our proposed approximate control variate framework recovers existing multifidelity variance reduction schemes as special cases. We demonstrate that existing recursive/nested strategies are suboptimal because they use the additional low-fidelity models only to efficiently estimate the unknown mean of the first low-fidelity model. As a result, they cannot achieve variance reduction beyond that of a control variate estimator that uses a single low-fidelity model with known mean. However, there often exists about an order-of-magnitude gap between the maximum achievable variance reduction using all low-fidelity models and that achieved by a single low-fidelity model with known mean. We show that our proposed approach can exploit this gap to achieve greater variance reduction by using non-recursive sampling schemes. The proposed strategy reduces the total cost of accurately estimating statistics, especially in cases where only low-fidelity simulation models are accessible for additional evaluations. Several analytic examples and an example with a hyperbolic PDE describing elastic wave propagation in heterogeneous media are used to illustrate the main features of the methodology.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Gas-solid reaction pathway for chlorination of rare earth and actinide metals using hydrogen and chlorine gas

Hydriding and chlorination of buttons of metallic cerium have been tested as a head-end step to separating metal impurities from actinides. The objective here was to achieve complete conversion to chlorides while maintaining high surface area via small particles and open porosity. Hydriding by reaction with 100% H 2 gas at 573 K was successful at reducing cm-scale metal buttons into small particles/fragments. This step was followed by reaction with flowing 99.5% anhydrous Cl 2 gas at temperatures ranging from 423 to 573 K for 60 min. In experiments reported here, up to 92% conversion to cerium chloride was achieved from reacting with the anhydrous chlorine gas. The final chloride product has high porosity coupled with small particle sizes (microns to 1600 μm), which makes it suitable for subsequent purification processes. Higher chlorine concentrations in the gas favor higher conversion to chloride. The optimal temperature to achieve high chlorination is 523 K. Oxygen is a minor impurity in the chlorine gas which appears to prevent complete chlorination from being achieved.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2020

Microstructure, hardness and cavitation erosion resistance of different cold spray coatings on stainless steel 316 for hydropower applications

There is an urgent need for repair of hydropower components that have undergone damage due to cavitation. Conventional repair methods involve melting of materials and can deteriorate material properties and cause distortion. This study investigated the relevant properties of different materials using solid phase processing—cold spray technology. Stainless steel (SS) 316, Inconel 625 and CrC-NiCr materials were cold spray deposited onto base metal SS 316, respectively. Cold spray achieved dense uniform deposits with low level porosity, and intimate contact between the deposit and the base metal was observed. Severe plastic deformation imparted during the cold spray process resulted in significant grain size refinement, nanostructured regions were observed in the deposits across the interfacial area. Cold sprayed deposits exhibited elevated hardness in contrast to that of the base metal SS 316. The cavitation erosion resistance of the deposits was evaluated with a cavitation erosion jet adhering to ASTM G134. Both SS 316 and Inconel 625 achieved better cavitation erosion resistance when compared to that of the SS 316 base metal, with the former exhibiting close to a 4 times improvement.

Jiang, Xiujuan↗
DOE OSTI2020

Experimental demonstration and performance evaluation of a complex fenestration system for daylighting and thermal harvesting

Two significant design strategies for mitigating building energy consumption are daylight redirection and solar energy harvesting. Effective daylighting implementation enhances the amount of useful natural light within a space and offsets the need for electric lighting. Solar energy harvesting systems can mitigate energy costs from mechanical systems by managing incoming thermal loads or capturing solar energy that can be used to supplement thermal systems in the building. While there are many available façade-based technologies that can perform daylighting or solar thermal energy harvesting, there remains a limitation in available systems that can perform both of them simultaneously. This paper, describes the design and experimental demonstration of a Liquid Filled Prismatic Louver (LFPL) system, which combines both energy-saving strategies. The LFPL system was installed in a south-facing room in New York City and evaluated for indoor daylight penetration and potential for thermal energy harvesting. Daylight redirection is achieved through the prismatic louver geometry and proper orientation, whereas thermal energy harvesting is achieved through IR absorption from the liquid (e.g., water) within the prisms. Daylighting performance was evaluated by illuminance measurements at key locations within the space, whereas thermal harvesting performance was evaluated through temperature measurements and thermal imaging analysis. We show that the LFPL system, with all prismatic elements oriented at the same angle, achieve a 2-fold and 8-fold enhancement in daylight redirection to the ceiling, for prism orientations of 10° and 20°, respectively. We also demonstrate the system’s capability to adjust to specific lighting needs, within the space, through the dynamic individual orientation of prismatic elements; thus, achieving a concentrated ceiling illuminance enhancement of ~100 times and ~200 times at 2.5 and 4.3 m away from the window sill, providing workplane illuminance enhancement of 6 and 2 times more than in the case of the control room with regular windows. Furthermore, we illustrate a reduction of potential heating loads at locations close to the window from the combination of infrared absorption in the water volume and the redirection of the incoming solar radiation, leading to a reduction of the workplane temperature by an average of 7–10 °C.

14 SOLAR ENERGY↗