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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Novel Engineering and Fabrication Techniques Tested in Low-Noise- Research Fan Blades

A major source of fan noise in commercial turbofan engines is the interaction of the wake from the fan blades with the stationary vanes (stators) directly behind them. The Trailing Edge Blowing (TEB) project team at the NASA Glenn Research Center designed and fabricated new fan blades to study the effects of fan trailing edge blowing as a potential noise-reduction concept. The intent is to fill the rotor wake by supplying air to the rotor blade trailing edge at the proper conditions to minimize the wake deficit, and thus generate less noise. The TEB hardware is designed for the Active Noise Control Fan (ANCF) test rig in Glenn's Aeroacoustic Propulsion Laboratory. For this test, the air is fed from an external supply through the shaft of the rig. It is distributed to the base of each blade through an impeller, where it is forced into a plenum at the core of each blade. In actual engine configuration, air would most likely be bled from the compressor, but only at times when noise is an issue, such as takeoffs and landings. Glenn researchers designed and manufactured the blades in-house, using new techniques and concepts. The skins, which were designed for maximum strength in the directions of highest stress, were molded from multiple layers of carbon fiber. Considerable use was made of rapid prototyping techniques, such as laser sintering. The core was sintered from a lightweight polymer, and the retainer was CNC-machined (computer numerical control machined) from aluminum. All the components were joined with a cold-cure aerospace adhesive. These techniques and processes reduced the overall cost and allowed the new concept to be studied much sooner than would be possible using traditional fabrication methods. Since this test rig did not support the use of blade-monitoring techniques such as strain gauges, extensive bench testing was required to qualify the design. The blades were examined using a variety of methods including holography, pull tests (cyclic and failure), shake tests, rap tests, and nondestructive inspection. Acoustic testing of the ANCF fan using TEB has been ongoing since January of 2001. The fan has completed about 100 hr of testing with no structural, vibrational, or fatigue problems. Far-field acoustic measurements, in-duct mode measurements, precise hot wire surveys, and detailed performance measurements are providing data for evaluating the concept. The far-field noise data show that tone noise was reduced significantly with the initial ANCF TEB fan design. In addition, a significant reduction in unsteady stator loading has been measured, indicating the potential for stator broadband noise reduction. The acoustic benefits will be assessed and important design parameters identified to improve the ability to fully exploit any benefit provided by this technique. On the basis of the success of trailing edge blowing, Glenn plans to continue this research with a higher speed, higher pressure ratio fan operating in an acoustic wind tunnel to simulate flight conditions.

Cunningham, Cameron C.↗
NASA NTRS2007

Noise Reduction Technologies for Turbofan Engines

Significant progress continues to be made with noise reduction for turbofan engines. NASA has conducted and sponsored research aimed at reducing noise from commercial aircraft. Since it takes many years for technologies to be developed and implemented, it is important to have aggressive technology goals that lead the target entry into service dates. Engine noise is one of the major contributors to the overall sound levels as aircraft operate near airports. Turbofan engines are commonly used on commercial transports due to their advantage for higher performance and lower noise. The noise reduction comes from combinations of changes to the engine cycle parameters and low noise design features. In this paper, an overview of major accomplishments from recent NASA research programs for engine noise will be given.

Huff, Dennis L.↗
NASA NTRS1994

High performance miniature hygrometer and method thereof

An uncoated interdigitated transducer is cooled from a temperature above the dew point to a temperature below the dew point, while a parameter of a signal of the transducer is measured. The reduction in temperature causes a monotonic change in transducer signal because that signal is sensitive primarily to the water loading of the transducer surface as water forms on that surface due to the reduction in temperature. As the dew point is approached with temperature reduction, the slope of the curve of transducer signal with respect to temperature, remains relatively constant. However, as the dew point is reached the slope of that curve increases and because of changes in the structure of the water layer on the surface of the transducer, at the dew point the transducer responds with a clear shift in the rate at which the transducer signal changes. The temperature at which the second derivative of signal vs. temperature peaks can be readily used to identify with extreme accuracy, the precise dew point. The measurement technique employed by the present invention is relatively immune to surface contamination which remains significantly unchanged during the brief measurement period.

VanZandt, Thomas R.↗
NASA NTRS2018

Formation Flight System Extremum-Seeking-Control Using Blended Performance Parameters

An extremum-seeking control system for formation flight that uses blended performance parameters in a conglomerate performance function that better approximates drag reduction than performance functions formed from individual measurements. Generally, a variety of different measurements are taken and fed to a control system, the measurements are weighted, and are then subjected to a peak-seeking control algorithm. As measurements are continually taken, the aircraft will be guided to a relative position which optimizes the drag reduction of the formation. Two embodiments are discussed. Two approaches are shown for determining relative weightings: "a priori" by which they are qualitatively determined (by minimizing the error between the conglomerate function and the drag reduction function), and by periodically updating the weightings as the formation evolves.

Ryan, John J.↗
NASA NTRS2018

ISRU Soil Water Extraction: Thermal Challenges

Water extraction from regolith requires significant energy input; heating efficiency is key to system power balanceRegolith has low thermal conductivityRecuperated heat from either reacted regolith or other systems merits examination, but must be done at the system model level (not component level)Water capture system may require significant reduction in temperature of the water vapor (e.g. condenser) Unknown parameters for modeling include:Residence time for water releaseConvection/conduction coefficients (sweep gas and/or flowing soil)Heat of dehydration for Mars hydrates.

Kleinhenz, Julie↗
NASA NTRSDate not supplied

Toward the fabrication of a 5 μm resolution Wolter microscope for the National Ignition Facility

Advancements in computer-controlled polishing, metrology, and replication have led to a x-ray mirror fabrication process that is capable of producing high-resolution Wolter microscopes. The mirror is a nickel-cobalt replicated full-shell mirror that was electroformed from a finely figured and polished mandrel. This mandrel was designed and fabricated for a 8 m source-to-detector distance microscope, with 10× magnification. A computer controlled polishing process corrected the low-frequency mandrel figure to < 2.0 nm RMS error. The mandrel design was optimized to reduce shell distortions that occur mainly < 20 mm from the shell ends. This design, in combination with improved replication tooling design and refined bath parameters informed by a detailed COMSOL model, have led to reductions in replication errors in the mirror shell. X-ray tests performed on a pair of mirror shells replicated from the mandrel have demonstrated < 10 μm FWHM source plane imaging resolution. Here we discuss the development process, highlight results from metrology and x-ray testing, and define a path for achieving 5 μm FWHM resolution.

Grazing Incidence, Wolter Microscope, X-ray Optics↗
DOE OSTI2020

Test for Reconditioning RA Waste with Simulated Bitumen and Concrete in a 1,2 MW Plasma Test Facility - 20092

The operation and maintenance of nuclear power plants, the non nuclear fuel cycle, etc generate low-level radioactive waste which, along with the historical radioactive waste from past nuclear activities, needs to be treated and stored, awaiting final disposal. Plasma technology offers a very effective way of treating this waste with a high volume reduction factor (VRF), free from organics, liquids and moisture, and meets without a doubt the acceptance criteria for safe storage and disposal. By means of a plasma beam of approximately 5000 deg. C, the inorganic materials are melted into a glassy slag, containing most of the radioactive isotopes while the organic material is gasified, oxidized and purified in an off-gas cleaning system. First the paper describes the new full-scale Plasma Melting Facility (PMF) at the Kozloduy Nuclear Power Plant in Bulgaria which was taken in nuclear operation In May 2018. The plant has a capacity of 250 tons per year and the maximum contact dose rates of the incoming waste is 2 mSv/h. Different mixtures of radioactive waste packed in 200 l drums were successfully treated resulting in a glassy slag free from liquids and organic material with an important volume reduction factor (VRF). The Project was co-financed through a grant by Kozloduy International Decommissioning fund (KIDSF) administrated by the EBRD through Bulgarian national funding. Plasma is a suitable technology for treatment of problematic waste or even reconditioning waste so Belgoprocess was contracted to do plasma tests with simulated conditioned waste types. One can do tests on a laboratory scale on smaller samples and torch capacities of e.g. 50 kW but Belgoprocess wanted to do more realistic and reliable tests. So Belgoprocess contracted Phoenix Solutions Co who has a full-scope test facility equipped with a 1200 kW plasma torch for full-scope treatment of simulated conditioned waste. For a first confidential contract simulated 200 l (55 gallon) bitumen drums were treated. The drums contained different pucks of compacted waste such as rags, used filters, granulates, etc. The pucks were stacked in the 200 l drums and subsequently embedded with bitumen. A total of 6 drums were treated in the plasma facility. For a second contract simulated homogeneous 200 l (55 gallon) concrete drums with on the one hand concentrates and on the other hand spent resins were selected. A total of 6 drums with concrete and spent resins were treated and melted in the plasma testing facility. The paper describe the test facility, volume reduction factor (VRF) of different waste streams and most important parameters. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1986

Magellan spacecraft - Attitude determination, updates and gyro parameter calibration

A detailed mathematical algorithm for onboard autonomous attitude determination and parameter calibration in the Magellan Venus-orbiting spacecraft has been developed, and its performance has been estimated. This algorithm uses a contamination reduction attitude profile and retractive star scan maneuvers to minimize the interparameter error contamination and to maximize the parameter observability. The details of the underlying theory and strategy are described, and an extensive performance analysis with worst-case parameter errors is reported which indicates that the in-flight attitude determination unit/parameter calibration (ADU/PC) algorithm will be able to meet all the different mission phase requirements with comfortable margins. The problem of nonexact mapping retrace due to uncertain performance of control authority is addressed, and its lack of impact on the system performance is demonstrated.

Huang, W. H.↗
NASA NTRS2010

Employing ISRU Models to Improve Hardware Design

An analytical model for hydrogen reduction of regolith was used to investigate the effects of several key variables on the energy and mass performance of reactors for a lunar in-situ resource utilization oxygen production plant. Reactor geometry, reaction time, number of reactors, heat recuperation, heat loss, and operating pressure were all studied to guide hardware designers who are developing future prototype reactors. The effects of heat recuperation where the incoming regolith is pre-heated by the hot spent regolith before transfer was also investigated for the first time. In general, longer reaction times per batch provide a lower overall energy, but also result in larger and heavier reactors. Three reactors with long heat-up times results in similar energy requirements as a two-reactor system with all other parameters the same. Three reactors with heat recuperation results in energy reductions of 20 to 40 percent compared to a three-reactor system with no heat recuperation. Increasing operating pressure can provide similar energy reductions as heat recuperation for the same reaction times.

Linne, Diane L.↗
NASA NTRS2011

Optimal Tuner Selection for Kalman-Filter-Based Aircraft Engine Performance Estimation

An emerging approach in the field of aircraft engine controls and system health management is the inclusion of real-time, onboard models for the inflight estimation of engine performance variations. This technology, typically based on Kalman-filter concepts, enables the estimation of unmeasured engine performance parameters that can be directly utilized by controls, prognostics, and health-management applications. A challenge that complicates this practice is the fact that an aircraft engine s performance is affected by its level of degradation, generally described in terms of unmeasurable health parameters such as efficiencies and flow capacities related to each major engine module. Through Kalman-filter-based estimation techniques, the level of engine performance degradation can be estimated, given that there are at least as many sensors as health parameters to be estimated. However, in an aircraft engine, the number of sensors available is typically less than the number of health parameters, presenting an under-determined estimation problem. A common approach to address this shortcoming is to estimate a subset of the health parameters, referred to as model tuning parameters. The problem/objective is to optimally select the model tuning parameters to minimize Kalman-filterbased estimation error. A tuner selection technique has been developed that specifically addresses the under-determined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine that seeks to minimize the theoretical mean-squared estimation error of the Kalman filter. This approach can significantly reduce the error in onboard aircraft engine parameter estimation applications such as model-based diagnostic, controls, and life usage calculations. The advantage of the innovation is the significant reduction in estimation errors that it can provide relative to the conventional approach of selecting a subset of health parameters to serve as the model tuning parameter vector. Because this technique needs only to be performed during the system design process, it places no additional computation burden on the onboard Kalman filter implementation. The technique has been developed for aircraft engine onboard estimation applications, as this application typically presents an under-determined estimation problem. However, this generic technique could be applied to other industries using gas turbine engine technology.

Simon, Donald L.↗
DOE OSTI2025

Development of Parameters for the Particle Size Distribution of TATB

Laser light scattering (LLS), manual counting of scanning electron microscopy (SEM) images, and reduction of SEM images using ImageJ (open source program) to determine Feret (caliper) diameters were applied to determine particle size distribution (PSD) of four preparations of 1,3,5‐triamino‐2,4,6‐trinitrobenzene (TATB) and yttria‐stabilized zirconia (YSZ), an SEM certified standard. Mie theory was used to reduce the LLS data. The spherical nature of the YSZ made it a good candidate for LLS. Variations in n , the refractive index, and iκ, the imaginary component, produced very little change in the PSD. However, changing the carrier liquid from H 2 O to a 40% aqueous sucrose solution, thereby changing the carrier refractive index, n 0 , substantially affected the PSD. The Mie complex refractive indices for the YSZ were n = 2.200, iκ = 0.100, with a 40% aqueous sucrose solution, n 0 = 1.400. The triclinic crystal structure of TATB made refractive index determinations more difficult, so a study was conducted varying Mie parameters and comparing them to the same data reduced using the Fraunhofer theory. Changing the n and κ parameters produced PSD with a small concentration of particles less than 1 µm in size or none in this range. SEM images, Feret data, manual counting, and Fraunhofer data reduction indicate particles less than 1 µm are probably < 5% in concentration. The final selection of Mie parameters for TATB was n = 2.283, iκ = 0.1, and suspension medium, n 0 = 1.330. Finally, computations, using density functional theory produced similar parameters.

Feret diameter↗
NASA NTRS2003

Numerical Simulation of High Drag Reduction in a Turbulent Channel Flow with Polymer Additives

The addition of small amounts of long chain polymer molecules to wall-bounded flows can lead to dramatic drag reduction. Although this phenomenon has been known for about fifty years, the action of the polymers and its effect on turbulent structures are still unclear. Detailed experiments have characterized two distinct regimes (Warholic et al. 1999), which are referred to as low drag reduction (LDR) and high drag reduction (HDR). The first regime exhibits similar statistical trends as Newtonian flow: the log-law region of the mean velocity profile remains parallel to that of the Newtonian ow but its lower bound moves away from the wall and the upward shift of the log-region is a function of drag reduction, DR. Although streamwise fluctuations are increased and transverse ones are reduced, the shape of the rms velocity profiles is not qualitatively modified. At higher drag reductions, of the order of 40-50%, the ow enters the HDR regime for which the slope of the log-law is dramatically augmented and the Reynolds shear stress is small (Warholic et al. 1999; Ptasinski et al. 2001). The drag reduction is eventually bounded by a maximum drag reduction (MDR) (Virk & Mickley 1970) which is a function of the Reynolds number. While several experiments report mean velocity profiles very close to the empirical profile of Virk & Mickley (1970) for MDR conditions, the observations regarding the structure of turbulence can differ significantly. For instance, Warholic et al. (1999) measured a near-zero Reynolds shear stress, whereas a recent experiment (Ptasinski et al. 2001) shows evidence of non-negligible Reynolds stress in their MDR flow. To the knowledge of the authors, only the LDR regime has been documented in numerical simulations (Sureshkumar et al. 1997; Dimitropoulos et al. 1998; Min et al. 2001; Dubief & Lele 2001; Sibilla & Baron 2002). This paper discusses the simulation of polymer drag reduced channel ow at HDR using the FENE-P (Finite Elastic non-linear extensibility-Peterlin) model which was used for the first LDR simulation by Sureshkumar et al. (1997). Flow and polymer parameters are close to realistic polymer drag reducing conditions. High drag reductions are achieved by using finite differences and a robust time stepping technique. A minimal channel flow is also used as a numerical experiment to investigate the effect of the outer region turbulent structures on the overall drag at HDR. The drag reducing action of the model is finally studied through the structure of energy transfers from the polymers to the velocity components. This investigation sheds some light on the details of polymer drag reduction.

Dubief, Yves↗
DOE OSTI2025

The SRG/eROSITA All-Sky Survey: Constraints on the structure growth from cluster number counts

Recent advancements in methods used in wide-area surveys have demonstrated the reliability of the number density of galaxy clusters as a viable tool for precision cosmology. Beyond testing the current cosmological paradigm, cluster number counts can also be used to investigate the discrepancies currently affecting cosmological measurements. In particular, cosmological studies based on cosmic shear and other large-scale structure probes routinely find a value for the amplitude of the fluctuations in the universe S​ 8 = σ 8 (Ω m /0.3) 0.5 smaller than the one inferred from the primary cosmic microwave background. In this work, we investigate this tension by measuring structure evolution across cosmic time as probed by the number counts of massive halos with the first SRG/eROSITA All-Sky Survey cluster catalog in the western Galactic hemisphere, complemented with the overlapping Dark Energy Survey Year-3, Kilo-Degree Survey, and Hyper Suprime-Cam data for weak lensing mass calibration, by implementing two different parameterizations and a model-agnostic method. In the first model, we measured the cosmic linear growth index as γ = 1.19 ± 0.21, which is in tension with the standard value of γ = 0.55 but in good statistical agreement with other large-scale structure probes. The second model is a phenomenological scenario in which we rescale the linear matter power spectrum at low redshift to investigate a potential reduction of structure formation, and it provided similar results. Finally, in a third strategy, we considered a standard ΛCDM cosmology, but we separated the cluster catalog into five redshift bins, measuring the cosmological parameters in each and inferring the evolution of the structure formation, finding hints of a reduction. Interestingly, the S ​8 value inferred from the number counts of the cluster eRASS1 when we add a degree of freedom to the matter power spectrum recovers the value inferred by cosmic shear studies. The observed reduction in the growth rate or systematic uncertainties associated with various measurements may account for the discrepancy in the S 8 ​ values suggested between cosmic shear probes and eROSITA cluster number counts and Planck CMB measurements.

cosmological parameters↗
DOE OSTI2025

LASSO for CALPHAD Model Selection Enables Data-Efficient Thermodynamic Modeling: An Application in Thermochemical Hydrogen Production Materials

Phenomenological CALPHAD (CALculation of PHAse Diagrams) models, widely used for multicomponent materials, often contain a considerable number of parameters and require fitting using data from a relatively small number of experimental measurements or theoretical calculations. Sometimes these parameters are introduced for the purpose of improving model fits but without clear physical justification, which leads to overparametrized models with poor generalization performance. Automated approaches for optimal model selection based on the available data therefore become critical. Here, in this work, a least absolute shrinkage and selection operator (LASSO)-based approach is developed for model selection by leveraging the linearity of the CALPHAD model with respect to its parameters to convert the model selection and fitting to a LASSO minimization problem. We demonstrate its utility for thermodynamic modeling of thermochemical hydrogen (TCH) production materials using lanthanum strontium manganite (LSM) as an example. Various TCH-relevant properties, including oxygen stoichiometry as a function of oxygen partial pressure, enthalpy of reduction, and entropy of reduction, are successfully predicted with reasonable accuracy using a minimal set of model parameters. Importantly, the model selection and fitting involve minimal human decision; it can therefore be applied to high-throughput DFT defect calculations and yield efficient workflows for TCH material modeling and optimization.

CALPHAD↗
DOE OSTI2025

MOOSE ProbML: Parallelized probabilistic machine learning and uncertainty quantification for computational energy applications

Here, this paper presents the development and demonstration of massively parallel probabilistic machine learning (ML) and uncertainty quantification (UQ) capabilities within the Multiphysics Object-Oriented Simulation Environment (MOOSE), an open-source computational platform for parallel finite element and finite volume analyses. In addressing the computational expense and uncertainties inherent in complex multiphysics simulations, this paper integrates Gaussian process (GP) variants, active learning, Bayesian inverse UQ, adaptive forward UQ, Bayesian optimization, evolutionary optimization, and Markov chain Monte Carlo (MCMC) within MOOSE. It also elaborates on the interaction among key MOOSE systems — Sampler, MultiApp, Reporter, and Surrogate — in enabling these capabilities. The modularity offered by these systems enables development of a multitude of probabilistic ML and UQ algorithms in MOOSE. Example code demonstrations include parallel active learning and parallel Bayesian inference via active learning. The impact of these developments is illustrated through five applications relevant to computational energy applications: UQ of nuclear fuel fission product release, using parallel active learning Bayesian inference; very rare events analysis in nuclear microreactors using active learning; advanced manufacturing process modeling using multi-output GPs (MOGPs) and dimensionality reduction; fluid flow using deep GPs (DGPs); and tritium transport model parameter optimization for fusion energy, using batch Bayesian optimization. These capabilities are part of the MOOSE framework.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Small Reactors in Microgrids: Technology Modeling and Selection (Net-Zero Microgrid Program Project Report)

This report demonstrates the capabilities of the net-zero microgrid (NZM) Xendee platform for modeling an SR module with electricity, heat extraction and thermal storage in microgrids configurations. The model effectively captures the most important technical and economic considerations for SR technology specific analysis: cost and operational characteristics of SR technology and financial costs and incentives. The model can analyze multiple scenarios to establish metrics for cost-competitive and zero-carbon microgrids connected to the grid or completely isolated. The model is fully integrated within the Xendee platform for modeling and analysis of clean energy microgrids with storage and generation from renewable energy sources. The model captures the capabilities, constraints, and nuances of SR by incorporating parameters related to plant economics, design efficiency and performance, plant operation and component and fuel lifespan. The cost and operational parameters modeled in the SR module are specific to the technology selected for integration in the microgrid. Cost parameters recognize advanced nuclear technology for modular production and installation based on economies of scale from factory manufacture and related commissioning, and cost reduction through technology maturation—first-of-a-kind (FOAK) and nth-of-a-Kind (NOAK). The cost parameters include installation, operations and maintenance (O&M), fuel refueling cycle, and reactor life. Installation cost reflects economies of scale due to unit sizing at scale and colocation. O&M economies of scale for both fixed- and variable-cost fuel life-cycle costs are incurred at every refueling interval, with separate front- and back-end fuel costs, as well as waste-handling and disposition costs. This report investigates key characteristics of different SR technologies suitable for microgrid applications, including design principles, sizing, coolant properties, temperature ratings, fuel structures, and life-cycle considerations. This also includes fuel technologies applicable to these SR systems, alongside strategies for nuclear-waste and spent-fuel management and approaches to address safety, security, and proliferation challenges. Four primary groups of SR technologies are examined: water-cooled, liquid-metal-cooled, high-temperature gas-cooled, and molten-salt-cooled systems. In this report, an initial guideline for technology selection is established, aligning the characteristics of the technologies with the requirements of microgrids. The selection of technology in a microgrid is influenced by various factors, including financial capacity, location and accessibility, demand type and characteristics, reliability and resilience requirements, area constraints, and the lifespan of the microgrid. The types of electrical and non-electrical applications within the microgrid also play a significant role in technology selection. The characteristics of SRs, such as their smaller size, modularity, transportability, long refueling interval, improved safety features, ability to operate in autonomous or semi-autonomous mode, and provision of high-grade heat, are particularly appealing for microgrids. Furthermore, a list of considerations for implementing SRs in microgrids is outlined. The SR model is created to be continuously improved with the acquisition of actual data on investment and operational costs, experience with supply chains, production at scale, and field deployments. In the near term, performance data on applications in microgrids will become available from lessons learned from laboratory tests, such as those planned for the Microreactor Applications Research Validation and Evaluation Project (MARVEL), led by Idaho National Laboratory (INL). The SR model incorporates scenario data and known SR design specifications, enabling technoeconomic analysis for SR deployment in microgrids. It specifically considers the distinctive attributes of SRs as generators in technoeconomic studies. SRs can be modeled and analyzed with generation from renewable-energy sources, energy storage, and flexible loads over a range of functionality and applications. This offers a comprehensive tool for feasibility studies, scenario development, and sensitivity analysis for “what-if” consideration of any range of assumptions about SRs in microgrids and other aggregations of distributed-energy resources, including virtual power plants.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Techno-Economic Analysis of Large-Scale Hydrogen Production from Solid Oxide Electrolysis Cell Systems

The objective of this study is to establish a detailed techno-economic analysis to assess the effectiveness of incremental technology improvements needed for solid oxide electrolysis cell (SOEC) technology to achieve the U.S. DOE’s Hydrogen Shot goal of hydrogen production at less than $1 per kilogram. The pathway considers incremental technology improvements to key system parameters, with system performance and cost assessed for each pathway step. Briefly, the steps include cell voltage degradation rate improvements, operational current density increases, operating temperature reduction, improved steam utilization, increased system capacity factor, and reduced cell/stack capital costs. Each step is assessed at both atmospheric and pressurized (8 bar) operating conditions. To supplement assessment at each of these discrete stepwise improvements, sensitivity studies are conducted to understand the relative impact of each parameter and identify avenues for additional cost reductions. System efficiency and levelized costs of hydrogen (LCOH) for each case are presented. For the end-of-pathway case, which includes all the incremental research and development improvements, the cost of hydrogen produced is reduced by 50 percent from the state-of-the-art case.

08 HYDROGEN↗
DOE OSTI2023

Extending Parsimonious Bayesian Inference

Parsimonious Bayesian inference is a theoretical framework for efficient data assimilation that seeks to balance increased consistency between predictions and training data against corresponding increases in model complexity. Within this framework, over-training is understood as optimization that encodes excessive information within model parameters while only achieving small improvements between predictions and training data. This project aims to develop practical methods of limiting excess model information during optimization. One key observation is that practical heuristics for parsimonious learning in high-dimensions must balance expressivity, i.e. the ability of the model to capture diverse predictions with only a few non-zero parameters, against discoverability, i.e. the ability to train the model with gradient-based optimization and drive parameters to low information states. As such, we developed logical activation functions that are able to adaptively approximate arbitrary truth tables that define Boolean logic operations within a probabilistic framework. These functions have demonstrated the ability to learn exclusive disjunction (XOR) and conditioned disjunction (if [condition] then [result_if_true] else [result_if_false]) within a single layer of a neural network. To efficiently exploit these activation functions to drive parsimonious learning required several other advances within the domain of variational inference. The most efficient form of complexity suppression is structured sparsification, driving most model parameters to zero while achieving the structural coherence among nonzeros needed for bandwidth reduction. Such models are not only far more efficient at suppressing information-theoretic complexity, they also reduce the other forms of complexity (computations, communication, storage, and the number of dependencies needed to evaluate predictions). Aiming to support enhanced sparsification, this project examined new approaches to high-dimensional variational inference that allow us to calibrate and control parameter uncertainty during optimization. By identifying which parameters can sustain sparsifying perturbations with little impact on prediction quality, we can develop better pruning strategies by framing them as approximate Bayesian inference. These advances also open paths to mitigate concerns with deploying advanced learning methods in resource-constrained environments, such as running models on power-limited or communication-limited devices.

97 MATHEMATICS AND COMPUTING↗